Optimal Engine Control for Series-Hybrid Electric Vehicles by Genetic Programming Methods

This paper addresses the problem of maintaining a stable rectified DC output from the three phase AC generator in a series-hybrid vehicle powertrain. In this case, the engine/generator combination is controlled by an electronic throttle, and the system as a whole can be represented as nonlinear with significant time delay. Previously, stable voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor, which rely on accurate system and time delay models, with associated computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist in the design of the control system. Firstly to maintain the internal combustion engine at its optimal operating point, and secondly to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the internal combustion engine under external load disturbances. In order to achieve these objectives, and reduce the complexity of implementation, in this paper a controller is designed by the use of Genetic Programming methods in Simulink, with the aim of obtaining a relatively simple controller for the time- delay system which does not rely on the implementation of real time system models or time delay approximations in the controller.