TesT and simulaTion CenTre for The eleCTriCal driveTrainThe test and simulation centre for the electrical drivetrain of the Fraunhofer Institute for Manu-

facturing Technology and Advanced Materials (IFAM) in Bremen bridges the gap between field

tests and simulations. Here, the electrical drivetrain is tested with load profiles recorded under

real conditions. The whole drivetrain or individual components can be verified, assessed and

optimised.

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Development TesTIng

SpecificationS

The scope of model-aided development in the electro-motive area is at the moment still heavily limited due to a general lack of experience in operation and usage. At the same time, real test data from proto-types and series-production vehicles is bringing in new knowledge and allows the development of more realistic simula-tion models. This allows shifting more sophisticated development and test tasks from the field into simulations and testing centres in the lab. The diversification of drivetrain concepts strongly increases at the same time the needed development and application work.

The first part of this article describes some typical tasks and requirements for the test centre. In the second part, we focus on the development and application of physical models of energy storage systems

characteriSticS of the Software uSeD

The control and analysis software is of great importance since it can be config-ured without deep programming know- ledge. Plain and simple, the software fol-lows the principle “configuration instead of programming” since it is primarily used by engineers and not by computer scien-tists. At the same time, it is flexible enough to be adapted to a wide range of tasks and hardware configurations.

The configuration of the test and simu-lation centre includes setting the parame-ters for the task to be executed and load-ing existing load profiles (e.g. recorded drive ). These are then modified (if neces-sary) and the sequence of the individual test and simulation steps is defined. For this the four possible operation modes: : operating point (manual control

through manual definition of operating points), ❶

: drive cycle : motor characteristic diagram : energy storage system test.are available. The set-up test can then be executed once or multiple times with a duration that can exceed 24 hours. Thextests can be controlled manually or automatically.

During the tests, measurement data from up to 100 channels plus the corre-

sponding control data can be recorded and stored on a local server.

For the evaluation and interpretation after the test end, we decided against standard reports since the requirements vary widely from test to test. The software offers every freedom for the mathemati-cal-statistical analysis and data represen-tation for documentation purposes.

The created evaluations are then com-piled into reports according to the test and simulation requirements. The result could for example be a recommendation to con-tinue the tests under defined modified conditions. Or suggestions can be offered for optimising the tested system or the tested components respectively.

electro-motive taSkS anD  requirementS

Compared with field experiments “on the street”, test centre experiments are cheaper, faster and can be repeated any number of times. Therefore, the test cen-tre’s prime objective is to reproduce real-istic operational conditions. One resulting sub-goal is to develop and test simulation models of components – e.g. energy stor-age systems (like batteries and super capacitors) – and optimise them in terms of their realistic behaviour. To create con-ditions which are as real as possible, the load profiles are recorded in real driving tests with electric vehicles. They can then be recreated in the test centre.

It is possible to test individual compo-nents of the drivetrain, multiple compo-nents at once or the whole system. Typi-cally, the components that are not physi-cally present are simulated, including a (complex) residual bus simulation of the rest of the vehicle.

It is possible to study and simulate energy storage systems, electric motors and their converters as well as control units, e.g. for an energy management sys-tem. The energy storage systems can be tested at a wide range of operational con-ditions, e.g. at environment temperatures from -40 to +140 °C. Electric motors can be tested individually or as a complete drive shaft including the motor control.

2 exemplarily shows the configuration of an energy storage system test. Here, energy storage units (in this case a battery system) are put into defined states (e.g. load conditions) and are stressed under

Dipl.-ing. StaniSlav vaSicis Project Manager electrical

systems and Head of the work group Test and simulation Centre electrical Drivetrain at the Fraunhofer Institute

for Manufacturing Technology and Advanced Materials (IFAM)

in Bremen (germany).

Étienne leDucis student Assistant at the

work group Test and simulation Centre electrical Drivetrain at the

Fraunhofer IFAM in Bremen (germany).

Dipl.-ing. rolf Spellmeyeris Application engineer in the field

of Test Centre Development and electric Motor Testing at

imc  Messsysteme gmbH in  Berlin (germany).

AuTHors

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defined environmental conditions (e.g. temperature) with simulated or recorded real load profiles.

When comparing a test centre for the electrical drive train with one for com-bustion engines, four differences become prominent: : First, there are the energy storage sys-

tems and the development of their models. As mentioned above, there are so far few tested and realistic models.

: From this, the second characteristic follows. To be able to correctly develop these models, very small voltage change (e.g. 0.3 V) has to be measured at very high electrical potentials (e.g. 1000 V).

: The very high voltages and currents (up to 1000 V and 600 A) in the electrical drivetrain also pose a challenge to the safety of the users. And the electrom-netic compatibility places high

demands on the signal transmission and the bus systems due to the high frequency of the converters.

: The last characteristic concerns the control of the test centre motors. Com-bustion engines are operated in only one quadrant, i.e. they only have on direction of rotation and provide torque. The load machine operates on torque regulation. Electrical motors on the other hand are operated in all four quadrants. They can deliver and absorb torque in both directions of rotation (feed back electrical brake energy).

Developing moDelS of energy Storage SyStemS

Here we describe how new models for simulating energy storage systems can be developed, regardless of the type of bat-tery. This approach was first tested with lead-acid batteries because they are pres-ently available in high numbers for a low price. Since then, the approach has also been successfully tried and tested with lithium-ion batteries.

In the first step, the battery chemistry and the electrical characteristics for the battery to be modelled are selected. The

❶ Manual control – complete manual control

Simulationof thebattery

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❷ Test of an energy storage system (e.g. load test of a battery system)

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basic conditions to be taken into account follow from the battery chemistry, like operating temperature and maximum currents as well as current and tempera-ture-dependent capacity characteristics.

In the second step, it is decided what should be simulated. During the first test of this approach this was the voltage-time-diagram as a function of the tem-perature and the chosen discharge cur-rent. This served to simplify and verify the applicability of the simulation soft-ware (MatLab/Simulink). The software presents several methods for modelling to choose from. We decided to use a physical model since it represents the individual battery components as electri-cal equivalent circuits and therefore an engineering approach.

In the third step, real energy storage systems were tested to obtain the data necessary for developing the model. In the pilot project, the battery in the envi-ronmental chamber was brought to dif-ferent temperatures. At each tempera-ture, several charge/discharge cycles were run. During the test design it should be taken into consideration that batteries need time to get into thermal electrical balance at the different temper-atures. This can restrict the amount of data that can be recorded, e.g. because of limited development time available.

In the fourth step, simulation and experiment are compared. The model is modified via systematic parameter opti-misation until it is as consistent as pos-sible with reality, 3. This is done in two phases.

During the first phase, the model is developed for a constant operating tem-

perature. To do this, a battery model is constructed (that for example may be available in MatLab/Simulink in a gen-eral form). Then the model parameters are varied in a wide range (0 to 1000 times the default value) to evaluate how much they each influence the curve pro-gression. Based on the results the para-meters with negligible influence are excluded. The other parameters are itera-tively modified by trial and error until they represent the real test results at a defined simulation quality (i.e. the ratio of simulation to reality).

During the second phase, the model that was developed for a single tempera-ture is expanded to include the values measured at other temperatures. To do this, the model is adapted in a way that the diagram crated for the first tempera-

ture only changes marginally. This is the prerequisite for obtaining a high simula-tion quality. To achieve this, it can be necessary to introduce new variables into the model’s equations, which influence the diagrams more strongly as a function of the temperature than the model origi-nally chosen accounted for.

At the end of step four, an optimised battery model is available. It can be used to simulate the battery at a specified tem-perature and current range for real time calculation in field tests, during actual operations or in the test centre. 4 shows the results for a lead-acid battery with an error of <1 %.

After the completion of all described steps, a model of an energy storage system that behaves realistically is available. It can help to test if different drivetrain topologies (e.g. different motors in different vehicle models) are suitable for different application scenarios (e.g. driving in the city, inter-urban rides and highway rides in dif-ferent seasons) – quickly and for low costs. Processes which change over time can also be modelled, e.g. the aging of cells in batteries or super capacitors. The particular advantage of a model is that you can always reset it to its original state. This prevents irreversible damage (e.g. through aging or damaging of cells) which in real energy storage systems might necessi-tate the acquisition of a new energy storage system.

Data of the real battery

Battery model forconstant temperatures

Extended battery model forvarious temperatures

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❸ Model development – step four

❹ Comparison of simulation and test for a lead-acid battery

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