Author Archives: Elora Zimmermann


FEV Battery Benchmarking

4. August 2020 | Featured Article

FEV Battery Benchmarking

Benchmarking offers unique opportunities for detailed insights into new technologies. Performance data, construction details, materials used, manufacturing processes utilized, and system functions can be analyzed using a detailed benchmark study. Vehicle and system tests provide crucial measurement data that provides information on the performance of new products. The dismantling of entire vehicles or individual technical systems shows the product structure and enables us to recognize necessary assembly processes.

Do you like to always to be a step ahead? The findings from specific benchmark programs help you to be that decisive step ahead in order to generate design and product ideas in interdisciplinary expert workshops. A neutral assessment of your own developments by a partner such as FEV provides you with that important external perspective.

In addition to the specification of technical product characteristics, the optimization of the cost structure is essential to developing competitive advantages. What is referred to as a “should-cost” calculation is carried out on the basis of a detailed analysis of the dismantled components. The should-cost analysis shows what the relevant product should cost with its current design and under the assumptions made. The results of the cost analysis provide insight into competitive costs and form the basis for defining target costs. As part of structured value analysis and cost reduction workshops, interesting cost reduction measures are determined that can be used to improve your own products.

For electric vehicles, the high-voltage battery represents a major cost item. Accordingly, a main focal point for the cost optimization of electric vehicles is the optimization of the battery. The benchmarking of battery systems newly launched on the market is an important part of the strategic development of the battery systems of the future.

In addition to the battery costs, technical benchmarking provides crucial insights regarding various performance aspects. An advance in energy density, and thus in range, represents a significant, unique selling point. Information on cell chemistry, battery management systems, and thermal management is important data that can be used for the further development of your own systems.

What do you need?

  • More in-depth insight into the latest technologies?
  • Understand the construction and functions in detail?
  • Important measurement data for performance parameters?
  • Understand the cost structure of your competition?

All batteries are not equal

In the automotive field, there are significant differences between different battery applications. Generally speaking, there are three battery types (Figure 1).

Figure 1: Main requirements per battery type (Status 2020)

The battery in a Mild Hybrid Electric Vehicle (MHEV) serves to power a 48 V onboard network and provides power capacities of up to 30 kW. The batteries of a Hybrid Electric Vehicle (HEV) offer power capacities of up to 200 kW and the batteries for Plug-in Hybrid Electric Vehicles (PHEV) provide, beyond that, an increased electric range and the option of external charging. For this battery type, energy and power density also play an important role. In contrast, traction batteries with high energy density are used for purely electric powertrains. Here, different cell types are to be used depending on the applications. In addition to the electric characteristics, these are also differentiated by design and cell chemistry. There are cylindrical, prismatic and “pouch” cells, as well as different cell chemistries, from the currently popular nickel manganese cobalt oxide (NMC) in various allocations, lithium titanate oxide (LTO), or lithium iron phosphate (LFP). Each technology has advantages and disadvantages with regard to power data, construction details, materials used, manufacturing processes utilized, total costs of ownership (TCO), and longevity.

Figure 2: specific gravimetric energy density at the pack level

If you now compare the respective gravimetric or volumetric energy density at the system level, larger differences appear due to cell selection, as well as module and system design. For electric vehicles, this consideration is an important distinguishing feature, since the energy density directly results in the range available to the client (Figure 3). For instance, if you compare newer BEVs, such as the Tesla Model 3 Long Range (2018) and the Hyundai Kona Electric 150 kW (2018), to each other, the differences are clear. The Tesla Model 3 Long Range has an energy capacity of 78 kWh with a battery weight amounting to 457 kg. By way of comparison, the Hyundai Kona Electric 150 kW has an energy capacity of 64 kWh with a battery weight of 452 kg. In the benchmarking comparison at the cell, module, and system level, the differences can now be assigned to technical measures. In this context, development teams can be provided with valuable information for future battery technologies.

In addition to the right cell selection and the construction details at the module and system level, thermal management plays an important role. There are different cooling concepts, from air cooling to indirect cooling using cooling sheets or cooling plates and water glycol, cooling via coolants, and direct cooling with dielectric fluids or the cells themselves (immersion cooling).


The high-voltage traction battery represents up to 50 percent of the total cost of ownership for battery electric passenger cars. It is thus fundamentally necessary to build a deeper understanding of the battery’s cost structure. The battery cells represent the main share of battery costs. In the example shown (Figure 3), the battery cells represent 64 percent of the total battery costs.

Modern battery electric passenger cars typically use lithium ion batteries with NMC (nickel manganese cobalt) cathode material. In particular, expensive material components, such as cobalt, drive the cell costs. One approach to optimizing battery cell costs accordingly consists in reducing the cobalt quantity. Figure 5 shows how, from a previously common uniform distribution (NMC-111), materials richer in nickel are developed (NMC-622, NMC-811, NMC-911). Using this type of optimization of the material composition, the cathode material costs can be reduced by over 40 percent. Further efforts in battery cell development aim to increase power density. A higher power density also means a cost reduction for the same battery range.

Figure 3: Design and cost structure of an exemplary BEV battery

Further cost drivers for the high-voltage traction battery are the module and battery casing components, thermal management, and the battery management system (BMS). After exceedingly complex constructions in the early battery generations, the benchmarking of the new battery generations now enables us to recognize clear approaches in terms of modularity and module structures. The goal is the achievement of scale effects and the simplification of the assembly processes.

Figure 4: Development of NMC cathode materials

In the end, the indicated approaches to cost reduction lead to further decreases in battery costs, and thus to an increase in the attractiveness of electric vehicles. While we are still seeing average battery pack costs for fully electric passenger cars amounting to approx. 180 EUR/kWh today, this value will decrease by half, to under 100 EUR/kWh by 2030. A battery with a capacity of 70 kWh will then cost less than 7,000 EUR instead of 12,600 EUR (Figure 5).

Figure 5: Battery cost evolution (average values) – Status as of 2019

Global FEV benchmarking

As a globally positioned development service provider with over 40 locations worldwide and many development centers, FEV offers extensive benchmarking services for their global clients. Dedicated benchmarking locations have been established in four core regions (Europe, USA, China, and India). Thus, local framework conditions and data can be taken into consideration, and global programmes can be run in parallel.

FEV has been conducting detailed benchmarking studies for more than 25 years. FEV uniquely combines in-depth technical expertise and cost engineering knowledge with strategic management consulting methods. The range of service provision includes extensive technical benchmarking, tear-down studies, cost benchmarking, and a benchmark academy; we also have access to extensive benchmark databases.

In addition to typical vehicle and system dismantling studies with professional photographic and video documentation, FEV engineers analyze the construction details, the functions, the materials, and the manufacturing processes. In order to carry out detailed performance and function tests, FEV has an extensive range of test systems: various on-road driving cycles, test tracks, vehicle test benches, and different system test benches – e.g. for combustion engines, turbochargers, transmissions, batteries, electric engines, fuel cells, performance electronics, and NVH (Noise Vibration Harshness) analyses.

In addition to the focus on the automotive industry, benchmarking programs are carried out for the commercial vehicle field, for agricultural machines and construction machines, and for other technical products.

In a typical benchmark program, FEV procures the target vehicle and equips it with the corresponding measurement technology. Initial tests regarding driving performance and energy consumption can be carried out as part of “micro benchmarking” without damaging the vehicle. For further detailed testing, special measurement technology is incorporated into the system to be analyzed. Specific driving cycles and driving tests on real roads, test tracks, or chassis dynamometers provide detailed measurement data. After the dismantling of the vehicle, FEV engineers place the main components to be analyzed on the test bench. These include the combustion engine, the transmission, the high-voltage battery, or the electric engine. Power characteristics are recorded and measurement data is transferred to FEV scatterbands in order to compare them with other measurement results in the FEV database.

After performance tests have been conducted, FEV Cost Engineering experts analyze materials, manufacturing and assembly processes and carry out a detailed should-cost calculation. The cost analysis provides an extensive cost breakdown and shows key cost drivers. Thanks to the achieved cost transparency, cost reduction ideas can be generated and target costs can be determined. FEV provides a unique overall package of benchmarking services with core findings for your developments and your corporate success.


Battery Electric Drives

FEV – Your strong partner for battery development

15. June 2020 | Featured Article

FEV – Your strong partner for battery development

High-voltage batteries are increasingly being used in the automotive field in the course of electrification as a means of reducing CO2 and pollutant emissions. This is taking form in the use of existing vehicle platforms within hybrid or plug-in hybrid concepts as well as on the basis of new, fully electric solutions.

Currently, automotive manufacturers are amending – or replacing – their vehicle portfolios with electrified applications. Furthermore, new companies are being established worldwide that develop and launch electric vehicles in various manifestations. Driven by this need for new technologies, there is a strong need for support in the development of high-voltage batteries, which FEV can provide from the first concept to serial production and, beyond that, up to recovery and recycling.

The mechanisms described are not exclusively limited to the automotive sector. For commercial vehicle, industrial, and marine applications as well, research is increasingly being conducted regarding how vehicles previously powered by combustion engines can be battery operated. Here, the focus is mainly on smaller commercial vehicles, building machines, or smaller boats.

These changes enable both established and new manufacturers to secure further market share. The resulting pressure on development, and mainly battery development, frequently presents a significant challenge to the manufacturers’ planning. In the current projects, electric drives and batteries are frequently being integrated into existing vehicle architectures (also called mixed architectures) which are build for both conventional and electrified drives. This leads to battery installation spaces with significant free-form surfaces and complex or two-tier battery structures. Such configurations significantly increase the effort and expense required for development with regard to cooling system components, high-voltage performance, low-voltage cable harnesses, understeering devices, holders, and fixing elements.

However, market pressure requires that battery development projects be carried out within the planned time frame, with no possibility for subsequent changes. Battery cells are the core of every high-voltage battery. These cells are the basis for the configuration of the modules that then determine the energy and power of the battery within the corresponding electric wiring.

The enormous increase in demand has considerably restricted the availability of the different cell types and products from different manufacturers. Smaller manufacturers in particular are faced with significant challenges with regard to ensuring cell availability for planned applications. The serial production of battery systems may also prove to be a hurdle within a given development activity. For smaller annual unit quantities in particular, an economically viable concept can be difficult to create under certain circumstances. All this can have a long-term impact on the evolution of development projects.

FEV provides support using its experience from many serial development projects, and can assess the individual situation early on and make corresponding proposals in order to create a stable basis for such a development activity. In this context, the FEV engineering portfolio covers all development activities as well as, when necessary, the identification, recommendation, and qualification of a production partner that will serially produce the battery for the client.


FEV Battery Portfolio

Extensive portfolio

FEV is capable of offering development services in different manifestations. The basis of the FEV battery development portfolio includes all necessary services for development, from the first battery concept up until serial production, and for providing support beyond.

If required, FEV is also a strong partner for small serial productions of battery systems and handles all the necessary process steps in this context for the preparation and subsequent serial production for batch sizes of up to 1,000 units per year.

Suitable solutions

Battery-powered electric vehicles will achieve high acceptance in the market when they are at least equal to conventionally powered vehicles in all points relevant to clients

  1. Range
    One of the primary requirements for clients is range. Clients do not wish to give up the advantages they are used to with vehicles that are powered by combustion engines. The range of electric vehicles depends directly of the available energy charge of the battery. However, since growing capacity also leads to an increase in the weight and volume of the battery, a gravimetric and volumetric energy density as high possible is desirable in order to offer a vehicle that continues to be attractive.

    To travel longer distances, the driver will be obligated to make a pit stop in order to recharge the battery. This cannot take significantly longer than with fuel-powered vehicles. Therefore, another requirement is the optimization of charging time via better quick-charging capacity. The overall capacity of the battery will increase in the future. According to current forecasts, this capacity will reach 50 to 75 kWh (mass market) or 80 to 120 kWh (premium segment). For an increase of the State of Charge (SoC) from approx. 10 to 80 percent, the charging time will also be likely reduced to 15 minutes (premium segment) or 30 minutes (mass market). This leads to charging performances of up to 350 kW, which must be provided by the infrastructure. The material compositions of the anode and the cathode are being further optimized in order to increase the energy density. Currently, a Si/C composite is used for anodes, while for cathodes, in contrast, the nickel ratio is being increased. In the long term, the solid-state battery possibly offers considerable potential. In order to optimize the quick charging capacity, the cell design (solid-state battery) can be adjusted and the thermal management can be further optimized. Furthermore, the connection and the contacting systems must also be improved with regard to current carrying capacity.
  1. Driving power
    Previous purely electric vehicles mainly showed restrained driving performance, thereby creating a first impression among clients. Current models must do away with these prejudices and offer clients driving comfort equal or superior to that which they are used to. To this end, good acceleration values and the possibility of repeatedly demanding maximum performance, as well as long-term travel at maximum speed without any restrictions whatsoever are all important criteria.

    In order to achieve such acceleration values, high maximum amperage values in the range of 1,200 to 2,000 A for 4 to 10 seconds are necessary. Strong currents for a period of 30 to 120 seconds are necessary for the repeated demand for maximum performance, as is high continuous current for travel at maximum speed. At the same time, the cells (approx. 50°C) or the lines (approx. 100 to 150°C) must be prevented from exceeding their maximum authorized temperatures.

    This requires the optimization of the current path from the active material of the cell to the inverter and e-engine. This includes, among other things, internal cell connection technology, plug systems, separation systems, and safety installations. The cells must be actively cooled (e.g. with water-glycol), and the lines must be passively or actively cooled (e.g. through heat pipes) to avoid overheating.
  1. Longevity
    Another current, significant challenge is the aging of Li-Ion batteries. In the past, clients have occasionally had to deal with negative experiences with regard to the longevity of Li-Ion batteries used in consumer products (for instance, laptop computers, smartphones, digital cameras, etc.). For modern Li-Ion batteries as well, the longevity depends on use, time, and temperature. If the usable energy charge in relation to the new status reaches 80 percent or less of State of Health (depending on the cell chemistry and manufacturer), use of the battery in battery electric vehicles is no longer sensible. If this is taken into account in the battery design (hardware and software), the battery can then later be used in a second life approach – e.g. as a stationary buffer battery.

    Currently, a Li-Ion battery in automotive applications can be used for 8 to 10 years. The aim is to achieve a medium-term duration of 15 years and a long-term duration of 20 years. In addition to calendar aging, cyclical aging must also must also be considered. Currently, said aging is between 150,000 and 250,000 km, until the Li-Ion batteries reaches 80% of SoH.

    In order to reduce calendar aging, the average temperature of the cells must be reduced with effective thermal management. Cyclical aging is equivalent to state-of-the-art cells with around 1,000 to 2,000 full cycles with 80 percent of discharge depth each. The optimal working range of the cells is between 10 and 25°C (parking) and 40°C (driving). FEV can prepare an assessment of the longevity for different stress and utilization profiles with simulations. Improvements in the stability of cell chemistry (electrolyte, coating, nanostructure of the electrodes, and other elements) are necessary for the optimization of cyclical aging in order to reduce irreversible processes (e.g. electrolyte decomposition, formation of a SEI coat).


  1. Safety
    Regarding the safety of high-voltage batteries, a distinction must be made between utilization safety (UtSa) and functional safety (FuSa). While safety in use is intended to guarantee that there are no safety risks when used as expected or misused, functional safety based on ISO26262 ensures that no safety risks occur in the event of electric function failure.

    Through utilization safety, risks are identified, assessed, and reduced with measures. The risks notably include thermal runaway, coolant leakage, high-voltage contact protection, and crash safety. If functional measures are taken for the avoidance of these risks, said measures fall under FuSa and must be robust, in accordance with Automotive Safety Integrity Level (ASIL) integrity. To prevent thermal runaway, a utilization safety first step is protecting the cells from overcurrent and overvoltage/undervoltage (overdischarge/underdischarge). In another step, the FEV functional safety concept additionally protects the cells using appropriate hardware (sensors, actuators) and software, in accordance with ASIL integration (A-D).


  1. Costs
    Currently, battery-powered vehicles are more expensive for clients than those that are equipped with an internal combustion engine with comparable product characteristics, mostly due to the battery. Optimistic forecasts predict that, by 2023/2024, the first electric vehicles will reach the purchase price of a comparable combustion engine model.

    For this reason, it is necessary to reduce the current high costs of cell production in relation to the energy charge in kWh/kg. On the one hand, this can be achieved with a higher energy density with almost the same amount of material used. On the other hand, raw material extraction, processing, production automation, and cost-reducing measures in cell design are necessary in order to decrease the resulting costs per kWh.

    A very promising measure for the reduction of the cell costs is the substitution of the relatively expensive raw material cobalt with the cheaper option – nickel – in the cathode. The higher nickel ratio also helps to increase the range, whereby the nickel ratio is gradually increased in the N:M:C ratio (Nickel-Manganese-Cobalt) from 111 to 532 to 622, and up to 811 (“High-Ni roadmap”). However, these measures represent a trade-off with stability and, accordingly, with safety and longevity, which cannot be neglected.

Target conflicts

Increasing the nickel content within the cell enables a longer range with short charging times. On the other hand, this increase also creates a thermally unstable system, which increases the security challenges. Furthermore, calendar and cyclical aging are increased, which reduces the longevity. However, the substitution of cobalt with nickel has a positive impact on costs. Due to the changed cell design, however, there is an increased risk of lithium plating and overtemperature during rapid charging, which can lead to loss of capacity and thermal runaway. Optimized rapid charging leads to a higher thermal load due to higher currents, which creates bigger challenges for safety. Furthermore, the higher currents lead to reinforced lithium plating, which restricts longevity.

To increase driving performance, the overall system is subject a higher current load. This increases the risk of an overload of the individual components, which can lead to a thermal event or the loss of insulation protection. Furthermore, the higher currents have an influence on cyclical aging as well as on calendar aging due to the higher average temperatures; this, in turn, leads to reduced longevity of the Lithium-Ion batteries. In addition, the lines and the (plug) connectors must be designed to be more robust, which leads to additional costs due to changes in material needs.

If security is increased, there will be additional costs, since further functional measures using hardware (sensors, actuators) and software (algorithms, functions) will become necessary. Larger security reserves in the battery management system can also limit maximum performance, performance reproducibility, and range.

FEV provides consulting with a team of internationally recognized specialists at various sites, OEMs, Tier 1 suppliers, and cell manufacturers or takes over entire projects as part of general development. Initial technical concepts are created and coordinated so that they can be specified in the series development process for the start of production. In addition to the resolution of the described target conflicts in development phases, prototype batteries and small serial productions can be reated and validated on our own test benches for cells, modules, and packs.



The key component of e-vehicles: the battery management system

14. June 2020 | Featured Article

The key component of e-vehicles: the battery management system

Battery management systems (BMS) are necessary for the precise monitoring and control of the key component in electric vehicles – the lithium-ion battery. Since 2006, FEV has been involved in the development of battery management systems and, with its experienced team, is a partner of choice for hardware and software development for BMS. The portfolio offered by FEV ranges from the development of individual complex software functions, such as State of Health (SoH) and the provision of a BMS development environment for research purposes, up to turn-key development of a complete, client-specific BMS solution including a necessary, functional safety concept. Here, the serial production-ready FEV BMS software and the proven FEV BMS hardware can be relied on. The uniqueness about this software and this hardware is that both black-box and white-box solutions can be made available.

The performance capability of batteries is influenced by the quality of the control in addition to the selection of suitable battery cells. For the battery management system, which is one of the core systems with regard to battery development, FEV started developing its own BMS control units as early as 2006 and now has its own modular BMS system in the fourth generation, which, depending on the project requirements, can be implemented efficiently, as well as combined in different ways. This includes the battery management unit (BMU), various cell monitoring units (CMU) for 12, 15 or 18 battery cells, as well as the isolation monitoring unit (IMU). In this context, the BMU is the central unit, which controls the CMUs, the decentralized measurement units.

With the development and protection activity in many projects with a variety of requirements and battery architectures, the hardware components have a B-sample degree of maturity and, in addition to use in prototypes, can be purchased as a white box for serial development. During this continuous development, the availability of the installed components is just as much a focal point as the technical maturity, whereby the topic of obsolescence management is also taken into consideration.

The fifth generation of hardware is currently in an advanced development phase. This generation is suitable, for instance, for installation in battery systems from 48 V to 800 V. Batteries with one or several strands, as well as switchable 400 V/ 800 V batteries, can be controlled and monitored with this. Another advantage of the fifth generation is the four CAN communication channels, as well as the support from CAN-FD, the wake-up via CAN and partial networking. In addition to CAN, the BMU has two LIN channels as well as many inputs and outputs in order to meet the various client requirements. Customized development as per client requirements for serial use is also part of the portfolio.

An individual CMU from FEV monitors the temperature and voltage of up to 18 battery cells. Thanks to our proprietary hardware development and the simple, modular design, the CMU can be rapidly adjusted for the development process of various battery configurations with little effort. During development, the topic of cost optimization was also considered. In this context, a decrease in components, such as plugs, as well as a reduction of the test and manufacturing effort is pursued.

For the development phase, with the Campus Controller, FEV has developed a freely programmable control unit that can take over the various functions of the BMS or other control units, including:

  • Bus simulation
  • Manipulation of sensor signals
  • CAN gateway
  • Fan speed regulation

In combination with the FEV “VISION” project, a Bluetooth-based visualization solution, the system is a high-performance tool for various development purposes.

In this project, FEV focuses on the topic of man-machine interface for prototype vehicles. On the one hand, “VISION” is made up of the real time-compatible CAMPUS hardware, which takes over CAN gateway functions in this context and, on the other hand, of a tablet with the corresponding app. The CAMPUS hardware takes over the role of the cybersecurity gateway and connects the CAN network of the battery or the vehicle via a Bluetooth interface with the tablet. This ensures that only the relevant messages are read or sent. The data connection is implemented bi-directionally so that, on the one hand, the relevant system information, such as the charge status of the battery, the power requirement and the rotational speed of the engine, can be displayed on the tablet and, on the other hand, so that the commands from various input instruments (e.g. buttons or sliders) can be sent to the vehicle control units. Using the wireless connection, the tablet can also be outside the vehicle for presentation purposes or handed over to interested parties in order to share technical data during test drives.

It is also possible to exchange information with internet servers and thus record measured data – for instance, using the internet connection of the tablet hardware.

FEV Vision: A Bluetooth-based visualization solution

The application software: crucial to the performance of the battery

The software of a battery management system is crucially important to the performance of the battery throughout the entire life cycle and has a direct influence on central characteristics of the vehicles – for instance, on the range for purely electric driving modes (PHEV, BEV). Furthermore, the BMS often takes over functions, such as charging times forecasts or the calculation of the available power, which can be seen directly by the client, thereby influencing the vehicle experience. A precise calculation of parameters, such as the State of Charge (SoC) as well as the State of Health (SoH), is the basis for an optimal exploitation of the battery system and is simultaneously very challenging, because these are values that cannot be measured directly. Furthermore, the software is an important component of the safety mechanisms that ensure the safety of the battery system during operation.

The FEV BMS software has been continuously developed since 2006 and, thanks to a modular architecture with lean, AUTOSAR-compatible interfaces, can be used with various BMS systems flexibly and with little effort. Thus, this software is already being used for various battery systems, from small 12 V and 48 V systems up to high-voltage batteries with flexible wiring options. FEV relies here on broad experience, since many projects require fulfilling the individual requirements of the respective client. These requirements arise, for instance, from differences in the E/E layout or the architecture of the battery or from the functional integration into the vehicle. Fundamentally, the software is divided into three components: application, safety, and base software.

BMS software architecture

The FEV BMS application software is developed in a model-based manner and includes features such as power/current release, charge regulation, SoC/SoH calculation, balancing, contactor control, and battery diagnoses. The software is used on both the FEV BMS hardware and the control units of client suppliers. The porting of the application software to other platforms has already been carried out in several (serial) projects and the interface has thus been continuously optimized in order to keep the adjustment effort as low as possible. This also applies to interfaces to the vehicle. All relevant values can be parameterized or calibrated; this is another decisive factor with regard to the flexibility of the software. Particular attention is paid to the topic of verification and validation of the software. Here, test methods and tools of the FEV Embedded System Test Center (FEST) are relied on, along with HIL test system for battery management systems, which can emulate up to 192 individual cells.

Safety lifecycle of FEV as per ISO26262

The FEV BMS base software represents a development for FEV’s own BMS hardware. The software achieves the connection to the hardware components of the BMU and the CMUs, as well as provides the application software with, for instance, the storage of values in a “non-volatile memory” along with measurement values and I/Os for various services.

In addition to the development of the BMS software, FEV also supports OEMs and suppliers in developing their own BMS application and/or base software.

Global life cycle for functional safety (FuSa)

The functional safety concept can be developed either for a specific vehicle or as a stand-alone product independent of any vehicle (“off-the-shelf components”). If the development is for a known vehicle, the development of the battery system is directly integrated in the FuSa life cycle of the overall vehicle. This is normally the case for FEV developments. In contrast, if the development takes place independently of any vehicle (“safety element out of context”), a portion of the FuSa overall life cycle for the battery is observed. The integration in the overall vehicle life cycle then takes place at a later point by the vehicle manufacturer. The assumptions must be reviewed with regard to validity and any necessary changes must be processed via change management.


Considered aspects
Functional safety deals with risks that may be triggered by potential malfunctions of E/E systems due to systematic software or random hardware errors. In order to develop the battery system in a sufficiently safe manner according to current standards, FEV complies with the development principles of the ISO 26262 standard. Certain hazards, such as those due to chemical hazards or electric shock, are only considered part of the functional safety if the hazard is directly caused by the E/E function. Applied to the battery system, this means that the prevention of electric shock is primarily covered by the high-voltage safety. HV insulation and touch protection therefore does not fall within the scope of functional safety. However, certain E/E functions can also serve high-voltage safety and, accordingly, fall within the scope of functional safety. This is the case for an HV system switch-off during an accident, since here, the measures taken by HV safety, such as insulation, may be damaged and therefore can no longer be considered sufficient.

Concept phase
During what is known as the concept phase, there is an assessment of the risks that could occur due to malfunctions in the implemented system functions. In the process, FEV follows the approach described in the figure. The result of this hazard analysis and risk assessment (HARA) is the safety goals for the system. The scope of the necessary risk reduction is determined by the ASIL, leading to a classification using the letters from A to D. A typical example of a safety goal for a battery system is “The system should prevent battery thermal runaway” (typically rated by FEV with ASIL C or ASIL D). These safety goals are top-level requirements. Based on these safety goals, a functional safety concept is developed which is described in the functional safety requirements. In addition to detection, the safety concept also includes the emergency measures to be initiated. The creation of the functional safety concept is frequently complemented by failure tree analyses.

FEV – risk assessment approach

Product development phase
The system development phase comes after the concept phase. In this phase, the functional requirements are translated into technical requirements. Accordingly, this step is carried out together with the development of the technical system architecture. During this phase, depending on the ASIL classification of the safety goals, failure tree analyses and FMEAs are required by the ISO26262 standard. This phase then leads to the HW and SW development phases, with the safety requirements being incorporated into these phases.

FEV Test Bench BMS (T-BMS) for battery and module test benches

The battery management system from FEV is also suitable for other applications, such as utilization on the test bench.
To this end, FEV has developed a universal BMS (T-BMS) for battery modules; an expansion for the testing of entire batteries is also possible.

The system is based on an FEV BMU and one or several FEV CMU(s), serving to record cell parameters and their monitoring, as well as to calculate other parameters such as State of Charge (SoC). In this context, client-specific functions for the calculation of the necessary parameters can be implemented in the T-BMS. All entered parameters can be transferred to the test bench in order to record, analyze, and utilization for the test procedure. The T-BMS can naturally be used with FEV battery test benches as well as FEV MORPHEE, which enables us to offer a complete solution (see page 30) for the testing of battery modules. Thanks to the easily adjustable CAN interface, however, the T-BMS can also be utilized with a variety of other test benches.

Via a graphical user interface it is possible to calibrate all essential
parameters of the system, such as the number of connected cells. This allows a simple adaptation to different test requirements.

FEV Test Bench BMS


The PPV as Innovative Solution for the Automobile Trend Car Sharing

Personal Public Vehicle (PPV)

22. January 2019 | Engineering Service

Personal Public Vehicle (PPV)

Shared mobility is currently regarded as one of the most important topics in the automobile industry. Like all future urban mobility concepts, it requires close integration with social future research. For new vehicle car sharing concepts, recording all factors that involve costs and analyzing them in regards to their influence on cost effectiveness and vehicle construction is critical. FEV, share2drive, and the FH Aachen (University of Applied Sciences), together work on the future vehicle classes of personal public vehicles (PPV) as a means of transportation and an interface between public and personal transportation.


The urban mobility trait (UMT),used in the context of shared mobility,describes relevant forms of urban mobility services from the perspective of individual mobility needs and assesses business models with special vehicle concepts. (Figure 1).

Fig. 1: Various personal mobility requirements according to the UMT

From this, it becomes clear that mobility services with free-floating car sharing consist of sharing vehicles that companies provide for their customers, who function as vehicle drivers. Generally, only a small number of people are transported by free-floating car sharing and the driving distances are generally less than eight kilometers. This differs from ride selling, which includes companies such as Uber or Lyft. For these services, private individuals offer chauffeur services with their own vehicles or vehicles leased through the service provider themselves. Ultimately, customer user needs decide which mobility service they make use of. In addition to the cost of the trip, the time required for users to reach their destination is important.The convenience of the service coupled with comfort and the potential added value experienced, such as being able to use the trip time for personal or business tasks, are also important (Figure 2).

New approaches are necessary for transportation services. Share2drive GmbH, headquartered in Aachen, Germany, is carefully following this innovative approach. This young company was formed as a spin-off from the Aachen University of Applied Sciences. Their goal is to provide advanced mobility concepts in the area of car sharing. One of the main parts of the business model is the PPV – a vehicle that was specially developed in cooperation with FEV and its subsidiaries for car sharing use.

Marketable vehicles for shared mobility

New mobility services with UMT have a disruptive influence on the existing value-added structure within the automotive sector. This is due to actors from the ICT and energy industries forging ahead on the mobility market, bolstered with new business models and established mobility service providers. At the same time, large Tier 1 suppliers in the automotive supplier industry are reorienting themselves to react to market changes, including emerging vehicle manufacturers. In addition to further diversification of vehicle models for end customers, we can expect OEMs to increasingly focus on vehicles for mobility service providers [1]. Various studies forecast that at least 10 percent of vehicles worldwide will be used for mobility services by 2030 [2].

The competition for car sharing vehicle models is apparent. Whether these vehicles are designed according to the concept of “sharing a vehicle” or those of “sharing a ride”, “driver on board” or “be the driver” will influence the vehicle’s UMT. Vehicle concepts are only marketable if they have solid market penetration and an attractive total cost-for-ride. For a new vehicle concept, this means that all factors involving costs must be recorded and analyzed. This includes the vehicles themselves, their maintenance, and expenditures for infrastructure, ICT andactual operation. These costs must be represented in a profitable business model and it is important to consider the influence of vehicle construction for each of the stated factors.

The PPV as a new approach for shared cars

The vehicles, including electric solutions, which have been used for urban mobility services thus far only fulfill their purpose to a limited extent because they were originally designed for end customer use. Fleet operators only make minor modifications to the vehicles, especially in the area of access opportunities. However, the focus on special requirements for urban mobility operators and vehicle users based on car sharing concepts is increasing. At the same time, vehicles for new mobility services in a multimodal world must be understood as “rolling devices.” Therefore, it is logical to develop the requirement profile of a “perfect” sharing vehicle from a mobility concept and business model, not by a conventional customer analysis as is normally done. These sorts of requirements came from car sharing operations and joint research from the Aachen University of Applied Sciences andCambio Aachen, as well as from publications from the German Federal Association of CarSharing e.V. (Figure 2).

Fig. 2: Vehicle requirements derived from mobility and business model needs; requirements came from car sharing operations in the joint research from the Aachen University of Applied Sciences and Cambio Aachen, as well as from publications from the German Federal Association of CarSharing e.V. 

The thought behind the concept of the PPV is to develop a realistic vehicle that does not follow the current trend of “weightless” show cars, but that is a timely answer to the shared mobility requirements of the future. The vehicle specifications created for the PPV 1.0 address European homologation. In package engineering, the development process follows a unified representation of the package information according to the European Car Manufactures Information Exchange Group (ECIE) Standard. This makes it possible to compare the ergonomic and technical vehicle packages across manufacturers. During hardware concept development, a modular, easily adjusted interior seat box is used to verify the challenging interior specifications. Functional goals, such as for crashes, are secured by appropriate simulations according to the finite element method with a program called LS-Dyna.

Dimensions and structure: The greatest challenge comes from the mobility standard of designing a vehicle in the M1 class. In this class, only vehicle lengths of under 2.5 m (diagonal parking allowed) and a width of approximately 1.7 m are allowed. At the same time, three people have to fit into the PPV 1.0 in order to serve 95 percent of all conceivable trips. The standard that the interior should offer a friendly, spacious interior is an additional design impediment. PPV is able to fulfill this challenge with a one-box design that includes three seat occupancy (1+2 seater) in one row. The power train is coordinated and highly integrated as an efficient package with the floor assembly. A new body shell concept allows the windshield to be placed significantly farther forward. An important design element for this is the restored A pillar and very large glass panels. Another component of the structural concept is the driver door. A new swinging or sliding door concept guarantees that opening the door is a first-class experience, even in narrow parking spots.

Design development: Before the design is actually developed, the design DNA of the PPV 1.0 is defined in an interdisciplinary development group. To do so, widely varying urban spheres of association are created first and approximately 250 draft designs are developed based on these associations. The drafts, which will be consolidated into two different concepts from the preferred association, will then lead to the final concept decision. After this step, the design is developed in a typical digital CAS (computer-aided styling) process before the targeted design DNA can be implemented into the final design. In summary, PPV can be referred to as the world’s smallest self-driving bus.

The design language of the interior concept is very different from the exterior and relies heavily on the reduced communication DNA from the bus design and the IT world. The number of operation elements for the PPV 1.0 was reduced to an absolute minimum and the focus was put on intuitive operation. The driver seat is characterized by a modern, digital user interface, and the climate control design is based more on the urban spaces mindset and not on classic vehicle construction. An interior cleaning concept optimized to the cost of each trip, appropriate variability from the two-seater bench, omitting joints that collect filth, surfaces from boat construction, a spray-on floor from railway vehicle design, and consistently omitting “unnecessary” storage areas distinguish the interior as genuine car sharing useable space.

The drive: The drive concept of the PPV 1.0 is mainly based on 400V technology that is well developed and absolutely suitable for electronically driven urban vehicles. The technical data is completely competitive with 45 kW of drive power in the front, a maximum speed of 120 km/h, and a battery pack of nearly 20 kW/h. The range is at 80 km, even under extreme conditions, and is verified by a specially developed car sharing cycle. According to the share2drive business model, this dependably reaches the approximately two hours of operation that are required daily. Flex share from share2drive guarantees that the wireless charging processes will not fail. The conceptual decision of the tandem electrical motor design with two small-diameter electrical machines in the front end is based on the advantages of the crash design, as well as the demand to provide an agile city vehicle.


Safety requirement: In addition to the numerous measures in place to avoid accidents, the PPV 1.0 is characterized by superior crash safety (Figure 3). The special challenge of concept development is mainly the design of the frontal crash requirements. The very short frontend forces the development into a radical structural design with four load path planes and controlled deformation behavior. With a total deformation of approximately 350 mm, a mean crash impulse of 31 g with approximately 60 mm of firewall penetration is reached. Deformations were kept away from the centrally designed battery structure in side collisions. Crash resistance is complied with almost 60 kN for the roof crush resistance test according to the FMVSS (Federal Motor Vehicle Safety Standards) 216.

Fig. 3: Crash security of the PPV for the EU market and for additional urban accident scenarios 


Production advantages: The body shell is a FlexBody, which is a body construction kit that allows the development of profile-heavy, lightweight bodies with a hybrid design for vehicle projects with less than 10,000 production vehicles per year. Body structures can be developed and prepared for production in a very short time with FlexBody by a standardized process, as well as stringent division of the profiles and nodes (Figure 4). The greatest advantage is the very low investment. Construction methods with steel-intensive, and extremely high-strength materials are primarily used for the floor assembly of the FlexBody for the PPV 1.0. Aluminum solutions primarily dominate in the frontend and in the structure. A ladder-integrated frame protects the centrally designed battery. The static torsional stiffness of the 140 kg body is at a high level, with a lightweight index of approximately 3. The body shell is produced in what are called Innofix single shot fixtures and is designed for using a newly developed injection gluing procedure. 7,000 PPVs are planned to be produced annually in a two shift operation.

Fig. 4: Structural concept – FlexBody as a multi-material lightweight body (source: Imperia) 

The PPV as solution for the mobility of tomorrow

Market development of new mobility solutions offers an interesting potential for concepts that merge mobility needs, new business models, and vehicle construction. The strong response to the PPV 1.0 offers an answer to future mobility needs in a shared economy until 2020, as a special vehicle solution has already initiated the PPV 2.0 “SVEN”.

In classic vehicle construction, the quickly advancing development of autonomous driving benefits customers with improved comfort and safety. However, autonomous driving functions greatly exceed this in a shared mobility world. In urban areas, they make the mobility of the population and its logistical implementation possible.

[1] Kaas, H.W.; et al.: Automotive Revolution – Perspective Towards 2030. How the Convergence of_Disruptive TechnologyDriven Trends Could Transform the Auto Industry. McKinsey & Company, 2017
[2] McKinsey & Company: Carsharing & Co.: 2030_über zwei Billionen Dollar Umsatzpotenzial. Pressemitteilung vom 09.03.2017
[3] Anthrakidis, A.; Jahn, R.; Ritz, T.; et al.: Urbanes eCarSharing in einer vernetzten Welt. SteinbeisEdition, 2013


Innovative and Full of Energy

Location Munich

19. January 2019 | Corporate

Location Munich

EVA Fahrzeugtechnik GmbH was founded in 1994 and has been a part of the FEV Group since 2017. In light of the increasing development work for the completely electric powertrain, especially on high-voltage batteries, EVA, a specialist for high-voltage batteries and e-mobility, complements the expertise of FEV in the Electronics & Electrification business segment.

For the development of high-performance high-voltage batteries, which must meet strict requirements regarding energy content, range, resistance, temperature resistance, weight, and costs, EVA has demonstrated its considerable expertise in this field through the construction of several prototypes in the stationary area.

In addition to energy storage, EVA has also made a name for itself among automotive and energy sector customers through innovative services and products for the entire electrification process, ranging from the first concepts to systems, components, integration, securitization, and loading infrastructure. Along with FEV resources, EVA uses its own testing laboratory, a prototype building, and technical documentation for this.

At three Munich locations, there are now more than 400 experts working for FEV and EVA.


Providing Software Features Quickly

System Development

3. January 2019 | Engineering Service

System Development

Modern vehicles are complex systems dominated by continuously evolving software functions and highly cross-linked architectures. With shorter development cycles and increasing cost pressure, new approaches are required to provide safe and affordable mobility solutions. This paper tackles this by merging known computer science techniques with state of the art methods of mechanic and electric engineering: systems engineering is consistently done in four layers while retaining agile efficiency at the same time. Model-based requirements replace written text. Besides cost reduction through maintainable and reusable documentation, this approach enables semi-automated test case derivation cutting down testing effort. For the development of BMW’s next generation electrified drivetrain efficiency and quality objectives can be achieved. Thus, cost, quality and adaptability targets can be met at the same time.

System and Software Business Model Evolution

Automotive system development is confronted with conflicting requirements on the one side and market conditions on the other. Customers require a quicker reaction of product development to new technical trends. This results in a shorter time-to-market dropping from average values of five years in the 1980s to three years in the 21st century [1]. Including upgrades and facelifts as well, this even drops to a level of one to two years. With each system upgrade, customers demand more functionality at a similar price level. If inflation is taken into account, this requires a required cost reduction of 4 percent every year pushing available development budgets to steadily lower levels [2].
However, concentration on cost efficiency does not resolve the trade-off to be made. Individual, mechanically driven vehicles are being replaced by integrated mobility systems including the electrified drivetrain, vehicle-wide functionalities, user experience and diverse traffic scenarios. The integration is realized by complex software systems. If these are developed with the same methods and processes as during the last decades, verification and validation effort will explode. E.g., the migration from a state-of-the-art adaptive cruise control function to an auto pilot results in a validation effort increase by a factor in the magnitude of 100,000 [3]. Test effort, prototype vehicles and hence validation costs explode at abovementioned budget restrictions. As a result, quality assurance is performed risk-based where taken risks result in an explosion of software recall campaigns in the past decade [4].
For deriving right countermeasures, the weaknesses in current system engineering need to be analyzed (Figure 1).
At the begin of the development of new functionalities, system requirements and system architecture are difficult to be completely defined top down – they are usually being elaborated bottom up during prototype sessions to identify a desired behavior. However, description methods are missing to document doubtlessly for all later stages what shall be contained in the system. As a consequence, the entire system architecture is usually described incompletely and is therefore not maintainable. An incomplete or even missing system architecture leads, of course, to weak requirements on system level. Bottom up function level requirements have to be defined without taking consistent system interfaces into account. This causes multiple requirement alignment loops and hence early delay of project milestones. Hence, on a software level, unit tests are defined without consistent system and functional requirements which leads to additional integration loops caused by object code mismatches.
On a component level, test cases are not complete, causing similar integration issues on the vehicle level. These are mitigated by applying large vehicle fleets with intense staff involvement: error identification time is increased through failure detection on system level only, cost limits require a prioritization of test maneuvers.

Fig. 1: Quality dilemma

Model-Based System based on Software Development Approaches

One main strategy to handle the mentioned conflicts between time-to-market, cost reductions, arising quality issues and the increased validation time on vehicle level is frontloading. This means it is necessary to increase the efforts in early development steps like requirements development, functional design and architectural design [5]. In fact, frontloading is not a new idea as it shall help to reduce efforts on the more cost-intensive verification and validation tasks on Hardware-in-the-Loop (HiL) level or vehicle level. Furthermore, frontloading is recommended by many standards like ISO/IATF 16949 and ISO 26262. However, it cannot be easily applied as it needs an interdisciplinary approach combining methods from known mechanic and electric engineering techniques as well as computers science approaches.
Model-based systems engineering focuses on a continuously evolving model-based development of architectures and requirements [6, 7, 8, 9]. While a systematic and semi-formal representation of requirements is more intensive in a first step, experience from large scale software projects shows an increased product quality. The higher quality of documents resulting from frontloading activities reduces following costs for validation significantly. High quality models will reduce communication efforts, inconsistencies between requirements and reduce the amount of defects and failures which would otherwise only be detected on later verification levels. An easier communication is especially important in the context of large teams, interdisciplinary exchange and collaborations with external partners and internal departments (aspects, which are all common in the automotive domain).
The System Modeling Language (SysML) is derived from the Unified Modelling Language (UML) which was introduced in the 1990ies [10, 11]. It provides a larger set of structural and behavioral diagram languages to specify systems from different viewpoints on different abstraction levels, but does not provide a concrete process or detailed guidelines which diagram types are to be used in which order or for which level of abstractions. Similar to EAST-ADL, BMW has proposed a model-based system engineering approach called SMArDT (“Specification Method for Architecture, Design and Test”) which comprises four levels: Requirements level, function design level, architectural level, hardware resp. software design level (EAST-ADL: vehicle, analysis, design and implementation level), as shown in Figure 2 [12].

Fig. 2: SMArDT methodology overview

SMArDT combines a systematic vertical refinement approach from layer to layer with a horizontal hierarchical composition from the context of the overall engine to specific modules. From layer to layer additional requirements are identified and derived from higher level requirements, where suitable, to establish a complete tracing (as demanded by standards like CMMI or ISO26262 [13, 14]). On the technical level a first separation between hardware and software aspects is performed, which are then implemented on the fourth level.
SMArDT supports a systematic step-by-step model-based requirement and function specification due to the four abstraction layers [15, 16]. In consequence, on each level the provided requirements and concepts are reevaluated and detailed, which – in terms of frontloading – ensures a very early verification and validation on the ongoing activities. Of course these steps are quite time-intensive but provide also high quality artifacts which can be used to significantly speed up the overall development process. The mentioned abstraction layers are applied for the structured documentation whereas the applied process is meant to be agile [17].
In the context of this paper we will focus on one of several possible new opportunities, which are provided by a high quality set of semi-formal models: the semi-automated generation of test cases [18, 19].

Semi-automated Test Case Generation

The function models on the second layer realized by activity diagrams, state charts and internal block diagrams provide already enough information to generate test cases for verification purposes automatically.
A corresponding process is illustrated in Figure 3.

Fig. 3: Overview test case generation

Based on customer models, like use case and context diagrams, defined in the first layer, activity diagrams and state charts are defined during the function specification. These function models are defined in cooperation of specifier and tester to ensure that functional aspects, like correct failure handling, are also included. Based on these models from the function layer test cases can be generated automatically to fulfill the path coverage criteria C2c [20]. In addition, the tester can configure specific aspects of the model, like specific input parameter or decisions, to manipulate the test case generation for context-related needs.
Exemplary activity diagrams, which are used for test case generation, are shown in Figure 4. Different activities or decision node can be classified to adjust the test case generation for specific needs (e.g. test step execution time/cost, requirements, decision coverage). As the activity diagram and internal block diagram of the function
layer are refinements of the use case and context diagrams of the customer value layer (see Figure 2) and the activity diagram is based on the functional architecture described by the block diagram, the generated test cases represent all the aspects defined on both layers.
To be able to generate test cases from activity diagrams or state charts, besides a correct use of the SysML language, the explicit definition of expected output needs to be defined on an abstract level. While this is common for state charts the activity diagram language has been adjusted to fulfill these needs. Besides these technical requirements, high quality semi-formal models, representing an abstract but distinct functional description, are necessary to generate test cases, which can be used to verify a system based on defined requirements. These models are provided by the process and guidelines provided by SMArDT.

Fig. 4: Additional effort for automated test case generation

During the system requirement and function specification phase labels from a keyword database are reused to define interfaces and conditional aspects. These keywords are mapped to concrete platform-specific signals and their specific test execution. During the data dictionary implementation step for each keyword (and related signals), a concrete test sequence is implemented to be able to perform the initialization and evaluation automatically. Combining the mapping between keyword and signal database (and their test implementation) with the semi-automated test case generation, the effort to define, setup and execute verification tests is reduced significantly. In addition, because of the neutral nature of customer and function models the generated test cases can be reused for different platforms.

Application: Project “MTSF”

SMArDT and the approach for semi-automated test case generation is currently used in an ongoing series development project to define BMW’s upcoming generation of electric drives. In collaboration with the FEV Europe GmbH and the Software Engineering Chair of the RWTH Aachen University additional modeling guidelines for function models have been identified to allow a semi-automated test case generation, called “Model-based Testing of Software-based Functions” (MTSF).
During the development, efforts have been monitored systematically to evaluate if the proposed expectations are fulfilled. In Figure 5, a first evaluation on five different functions is shown, which highlights the additional effort on function specification level for specifier and tester to be able to derive test cases.

Fig. 5: Reduced effort due to MTSF

In relation to the complexity of the function the amount of effort, but also the amount of generated test cases, is increasing.
Function A is the first measured function including diagnosis and safety aspects and thereby highlighted the additional benefits in the context of these areas. As a path-wise test case generation requires logical branches to increase the amount of test cases, error detection and handling mechanisms highly increase the potential for automated test case generation.
Regarding the measured efforts it needs to be considered that the additional guidelines for test case generation have been applied the first time in a serious development context. Thereby, reduced efforts can be expected once the approach is established. In addition, not only the effort could be reduced, but also the quality of models is increased, because of the semi-formal nature of the introduced guidelines.
Nevertheless, comparing the measured efforts with ongoing traditional development, the expectations can already be matched, as reduced efforts on requirement interpretation and verification tasks are already negating the additional efforts on function specification level as shown in Figure 6.
Based on the current experiences further improvements on the test generation configuration are already identified to increase the quality of resulting test cases even more.
The overall process is supported by an integrated toolchain as represented in Figure 7. A fluent connection between the tools DOORS, PTC, ECU Test and HPQC is established to sustain the ongoing industrialization.

Summary and Outlook

The MTSF system engineering approach tackles the current conflict between solid requirements, test case and architecture definition for complex systems and cost and time pressure due to mobility market conditions. The method bases on model-based description of system functionalities through clearly defined abstraction levels. Semi-formal description enables efficient requirement alignment and semi-automated test case generation.
In this article, the design on the higher abstraction levels was focused sharing application experiences for the next generation of BMW’s electrified powertrains. For the first time, model-based specification was applied to system level development of automotive series products. Driven by a systematic function architecture definition, more than 50 functions reflect the designed behavior of energy management, charging and torque provision. Considering coverage criteria, test costs and execution time, test cases were derived semi-automatically for defined model paths. At the end of the workflow, automatically executable test sequences were produced.
The overall development effort could be reduced while working within given market and product milestones. Even more importantly, system quality is increased. More test cases are defined, test coverage can be determined in early stages, bugs can be identified at earlier design stages. Also, requirements, test cases and development artefacts can be aligned easily and traced doubtlessly.
Next steps will include the continuation of system development on lower abstraction levels. Quality gains will be observed – when reaching the vehicle test level, a significant reduction of prototypes and debugging phases is expected. The MTSF method will be expanded application-wise to other vehicle development domains outside the powertrain. Also, Failure-tree-analysis for e.g. safety applications will be facilitated. Next method development steps will focus the industrialization for large, distributed and cross-enterprise development teams. Here, we especially expect further work on bridging established development cultures of computer and engineering science domains.

[1] Prasad, B.
Analysis of pricing strategies for new product introduction
Pricing Strategy and Practice,
Vol. 5 Issue: 4, pp.132-141
Bingley (UK), 1997
[2] Mohr, D. et al.
The road to 2020 and beyond: What’s driving the global automotive industry?
Mc Kinsey & Company, Inc.
Stuttgart, 2013
[3] Hübner, H.-P.
Automatisiertes Fahren –
Wohin geht die Fahrt?
Proc. 18. Kongress Fortschritte in der Automobilelektronik
Ludwigsburg, 2014
[4] Steinkamp, N.
2016 Automotive Warranty & Recall Report: Industry Insights for the Road Ahead, Chicago, 2015
[5] Kriebel, Stefan
Economic High Quality Software for Automotive Systems
3d Congress on Real Time, INCHRON; Braunschweig 2011
[6] Wymore, A. Wayne
Model-Based Systems Engineering CRC Press, Inc. USA, 1993
[7] Estefan, Jeff A.;
Survey of Model-Based Systems Engineering (MBSE) Methodologies
Incose MBSE Focus Group 2007
[8] Grönniger, Hans et al.
View-Centric Modeling of Automotive Logical Architectures
In: Tagungsband des Dagstuhl-Workshop MBEES: Modellbasierte Entwicklung eingebetteter Systeme IV. Informatik-Bericht 2008-02, CFG-Fakultät, TU Braunschweig, 2008
[9] Kriebel, Stefan
Timing propagation in the development of software-based automotive systems 4th Symtavision NewsConference on Timing Analysis, Braunschweig
[10] Weilkiens, Tim
Systems Engineering with SysML/UML: Modeling, Analysis, Design Morgan Kaufmann, USA, 2008
[11] Rumpe, Bernhard
Agile Modeling with UML: Code Generation, Testing, Refactoring
Springer International
Germany, 2017
[12] Cuenot, D. et al. Managing Complexity of Automotive Electronics Using the EAST-ADL 12th IEEE International Conference on Engineering Complex Computer Systems 2007
[13] Paulk, Mark
Capability Maturity Model for Software, John Wiley & Sons, 2002
[14] Hillebrand, Martin
Funktionale Sicherheit nach ISO 26262 in der Konzeptphase der Entwicklung von Elektrik/Elektronik Architekturen von Fahrzeugen KIT Scientific Publishing, Germany, 2012
[15] Grönniger, Hans et al.
View-Centric Modeling of Automotive Logical Architectures
4th European Congress ERTS – Embedded Real Time Software, Toulouse, 2008
[16] Grönniger, Hans et al.
In: Proceedings of the Object-oriented Modelling of Embedded Real-Time Systems (OMER4) Workshop, Paderborn, 2007
[17] Linz, Tilo
Testen in Scrum-Projekten Leitfaden für Softwarequalität in der agilen Welt dpunkt.verlag, 2. Auflage 2016
[18] Pretschner, Alexander et al.
Model-based testing for real. STTT 5(2-3): 140-157, 2004
[19] Philipps, Jan et al.
Model-Based Test Case Generation for Smart Cards.
Electronic Notes in Theoretic Computer Science 80: 170-184, 2003
[20] Liggesmeyer, Peter Software-Qualität: Testen, Analysieren und Verifizieren von Software Spektrum Verlag 2009

This article is an excerpt from the publication: “1. Kriebel, S., Richenhagen, J., et al.: High Quality Electric Powertrains by model-based systems engineering.
Published in: Proc. 26th Aachen Colloquium Automobile and Engine Technology (2017), Vol. 1, pp. 211-222, ISBN 978-3-00-054182-7 “


Tailored Functional Saftey Process For Prototype Vehicles

Functional Safety

2. January 2019 | Engineering Service

Functional Safety

For the functional safety of series production road vehicles, the standard ISO26262 specifies a comprehensive development process from concept to production. For prototype and demonstrator vehicles, no dedicated functional safety standard is available and ISO26262 is not applicable, because the development efforts would by far exceed the scope of a prototype build-up. Nevertheless, it is necessary to consider functional safety for prototype vehicles in order to protect operators, passengers and persons nearby the vehicle from any harm caused by a malfunction. An according documentation is essential, because it proves that the safety has been taken into account and safety measures have been implemented.
Therefore, FEV has developed a tailored functional safety process for prototype vehicles, which is based on the main tasks as defined in the concept phase of ISO26262, but with reduced complexity. These tasks are the preliminary item definition, a high-level hazard analysis and risk assessment and the definition of safety mechanisms which shall be implemented in the prototype vehicle. Furthermore, an iteration loop is included in the process, in order to re-assess the remaining risk in combination with the defined safety mechanisms (Figure 1).

Fig. 1: Iterative process for risk mitigation by safety mechanisms

Preliminary item definition

In this article, the transformation of a conventional powertrain into a P2 hybrid powertrain is chosen as an example for the prototype application. Besides the integration of a high-voltage system, the powertrain modification itself is safety-related, too, as will be shown for one its main functions, electric driving. The preliminary item definition describes all functionalities, operating modes, interfaces and operating conditions of the system of scope, i.e. the P2 hybrid system in our example. This information is an essential input for the identification of potential risks resulting from malfunctions of the item.

High-level hazard analysis and risk assessment

Main steps of the hazard analysis and risk assessment (HARA) are the selection of relevant use cases for the prototype vehicle, the functional hazard analysis (FHA) and the risk assessment of the resulting hazardous situations. The FHA assigns standard malfunctions (does not, too much, not enough, wrong direction/distribution, unintended, stuck) to each function. Combined with the respective use cases, these malfunctions result in hazardous situations. One example for the e-drive function of the prototype vehicle is:

  • Function: Electric drive
  • Use case: Vehicle is stopped at red traffic light or at cross roads
  • Malfunction: Unintended torque
  • Hazardous situation: unintended vehicle movement, resulting in crash with crossing vehicle

The risk assessment of such a hazardous situation is based on three criteria as defined in ISO26262. Exposure (E) represents the frequency of the use case – not of the hazardous situation. Severity (S) is the rating for the harm that can be caused to somebody. And controllability (C) is a measure for the ability of the vehicle driver to avoid the hazard by his intervention. Since the exact determination of these criteria is quite time-consuming, a simplified, conservative rating catalogue is applied for the prototype application and a risk level is calculated instead of an Automotive Safety Integrity Level (ASIL) as defined in ISO26262 (Figure 2).
The initial rating for the above mentioned example will be as follows:

  • Exposure for standing at traffic light / cross roads: E = 3
  • Severity for crash with crossing traffic: S = 3
  • Controllability for unintended movement: C = 2

The C-rating is depending on certain boundary conditions. In the example, the maximum wheel torque that the electric machine can generate is lower than the brake torque which the vehicle driver can realize by pressing the brake pedal. If such boundary condition is not fulfilled or if it cannot be ensured, a more conservative rating has to be chosen.

With E + C = 5 and S = 3, a “Medium” risk level is resulting, which requires safety measures as described in the following paragraph.

Derivation of safety measures

In order to achieve the risk level “Acceptable”, safety measures have to be defined for the risk levels “Low”, “Medium” and “High” as shown in Figure 2.

Fig. 2: Simplified rating scheme for the risk evaluation

For example, the “Medium” risk level can be reduced to “Acceptable” by several steps. The first step is the installation of an emergency stop button, which switches off the electric propulsion system. The driver has to be trained in its use, e.g. by inducing the fault on the test track. Only trained drivers will be allowed to operate the vehicle in urban traffic, which has to be documented e.g. by an according logbook in the vehicle. The C-rating is reduced from 2 to 1 with this measure. This will result in a “Low” risk according to Figure 2, so that an additional measure is needed. For example, the use of the prototype vehicle could be restricted to drive cycles with less than 1 percent of operating time at traffic lights and cross roads. This would reduce the E-rating from 3 to 2, resulting in an “Acceptable” risk. Since the example described in this article represents only one situation out of numerous other scenarios, there might be other risks that are rated as “High” and therefore demand further safety measures like monitoring algorithms. Such safety measures could then also be used for the mitigation of lower rated risks and allow to avoid restrictions like the limitation of use cases or operation of the vehicle by trained drivers only.

Fig. 3: Risk level and type of safety measure

For the completion of the simplified functional safety process, it is important to ensure that the defined safety measures are implemented and tested before the actual investigations with the prototype vehicle start. This can be supported by check lists and tests of the vehicle on the test track.
Besides the achievement of technical targets, a strict compliance with a safety-related development and release process is mandatory also for prototype applications. FEV has developed the described prototype process for this purpose and successfully applied it in several projects.


Know-How for ADAS - From System Architecture Design to Serial Validation

Location Poland

10. December 2018 | Corporate

Location Poland

FEV Poland started its work in 2003 with eight young engineers in a small office in Krakow – a central location for the domestic automotive and mechanical engineering industries and in close proximity to the local universities. The group’s initial focus was on engine development and software development was gradually added as a research focus. This has resulted in strong expertise in the fields of computer simulation and software development, which FEV Poland contributes to international projects within the FEV Group.

FEV Poland thus also gained valuable insights into the future topics of autonomous driving and advanced driver assistance systems (ADAS), which are now reflected in a broad service offer and full-service solutions, from system architecture development to serial validation. In addition to ultrasound and radar, lidar and camera systems with situation detection software, for instance, can also be integrated, tested, and validated. Validation takes place as part of a testing program that adheres to standards that apply worldwide and uses the latest measurement technology, including driving robots and high-precision positioning systems. Various test dummies and platforms are also used at this stage in order to test the interaction between autonomous driving vehicles and the environment to ensure the smooth function of the ADAS components and systems.
Since the foundation of FEV Poland, the number of employees has also grown, to more than 80. To provide the experts with the best working conditions, a move to a new building in Krakow occured last year.