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The quality of the powertrain design has a significant impact on the fuel consumption and emissions of hybrid vehicles. Lack of experience with these relatively new technologies, the enormous variety of hybrid powertrain configurations, and the multitude of components make this area an ideal application for computer-based modeling and optimizations. Global optimization techniques have the advantage to explore systematically the design space to find the optimal configuration space. In this paper, a systematic procedure for an optimal design of hybrid powertrain configurations using an evolutionary algorithm is proposed. It will be shown that the design steps for parallel and power-split configurations are quite similar. This results in a computing approach with high synergy effects and the ability to exchange components seamless to compare different ‘virtual’ configurations.

For compliance with future more stringent emission standards exhaust emissions must be reduced. One possibility is to improve air-fuel ratio control quality. The approach presented in this paper uses virtual sensors to get a rough picture of the spatial distribution of lambda and oxygen storage states across the catalyst. This additional process information is gathered by means of a novel model for three-way catalysts. A state-space controller is used to maintain oxygen storage states predicted by the model at desired levels. The proposed control strategy has been implemented on a turbocharged, direct injection engine and successfully validated by means of emission measurements. A comparison with a commonly used air-fuel ratio control strategy is presented.

In power-split configuration, the input power is split into two parts, one of which is transmitted from the internal combustion engine through one or more planetary gear(s) to the wheels. The other part is generated as electricity and passes through an electrical variator to assist the driving torque. The latter has the characteristic of poor efficiency. In this simulation study, a comparison among the input power-split, compound power-split, and two mode power-split are discussed. Output power-split is not mentioned in this paper due to its limited applicability in specific vehicles. The idea of selection of the electrical machines is explained: the speed and torque of electrical machines was taken into consideration for the required transmission ratios spread.

This paper proposes a current limits distribution control strategy for a parallel hybrid electric vehicle (parallel HEV) which includes an advanced powertrain concept with two electrical driving axles. One of the difficulties of an HEV powertrain with two electrical driving axles is the ability to distribute the electrical current of one high voltage battery appropriately to the two independent electrical motors. Depending on the vehicle driving condition (i.e., car maneuver) or the maximization of the entire efficiency chain of the system, a suitable control strategy is necessary. We propose an input-output feedback linearization strategy to cope with the nonlinear system subject to input constraints. This approach needs an external, state dependent saturation element, which translates the state dependent control input saturation to the new feedback linearizing input and therefore preserves the properties of the differential geometric framework.

Due to the integration of many interacting subsystems like hybrid vehicle management, energy management, distance management, etc. into the VCU platform the design steps for function development and calibration become more and more complex. This makes an aid necessary to relieve the development. Therefore, the aim of the proposed simulation-based development and calibration design is to improve the time-and-cost consuming development stages of modern VCU platforms. A simulation-based development framework is shown on a complex function development and calibration case study using an advanced powertrain concept with a plug-in hybrid electric vehicle (PHEV) concept with two electrical axles.