Development Process for Operational Strategies of Electric Vehicles with Range Extender

Current electric vehicles have the distinct disadvantage of a short operating range and the need of a time-consuming battery charge procedure compared to conventional vehicles. To overcome these drawbacks an additional internal combustion engine to extend the operating range (so called Range-Extender) can be used. The Range-Extender as modular part of an series hybrid powertrain offers the potential to compensate the disadvantage and to increase customer acceptance. Therefore it is a promising technology for the breakthrough of electric vehicles in the segment of micro and small cars. Operation and application of Range Extender electric vehicles differ with respect to other propulsion concepts, such as Plug-in hybrid vehicles. Differences are known especially in the way of distributing power to the energy converters and their frequency of operation. Consequently, the operational strategy must be adapted to the corresponding concept to meet conflicting demands of fuel or energy consumption, engine emissions and acoustics as well as driving comfort in the most optimal way. In this area FEV uses a continuous development process for the design of operating strategies of hybrid powertrains from concept to series vehicle. With specific powertrain simulations, considering the general system requirements and all relevant component data, the required drive power for various driving cycles is determined. Furthermore a numerical optimization method, computes the optimal operational strategy for the selected driving cycle. Depending on the considered parameter the optimization result could be for example the most efficient or lowest noise operation of the Range-Extender vehicle. Other methods only determine the vehicle operational strategy by varying parameters of a rule-based strategy. But there remains an uncertainty of the achieved result with respect to the theoretical optimum. In contrast the presented approach computes the global optimum within given boundaries. Thus, the result will be used as reference for the design and implementation of a rule based operation strategy in further software development. Rule-based operation strategies offer significant advantages in terms of a simple and transparent calibration compared to other alternatives (such as on-line optimization strategies). Additionally, a comprehensible system behavior to the driver can be guaranteed at any time. In the same way the quality of a rule-based control strategy can be easily assessed by comparing its results to the previously computed optimal operation. Therefore this approach reduces the loss of potential. In addition, the integration of further functions such as a catalyst-heating strategy or functions that use noise masking effects is simplified. After integration on the target control unit the powertrain simulation model can be reused to validate the operation strategy within Hardware -in-the-Loop (HiL) tests. Finally vehicle testing ensures mature software and completes the vehicle development process.