Real-time Adaptive Heuristic Control Strategy for Parallel Hybrid Electric Vehicles

In this work, a new rule-based control strategy is developed for the energy management of parallel hybrid electric vehicles (HEVs): the torque-leveling threshold-changing strategy (TTS). In contrast to the commonly used electric assist control strategy (EACS) designed based on the load following approach, the TTS proposes and applies a new fundamental concept of torque leveling. This mechanism operates the engine with a constant torque when the engine is active, thus ensuring the engine works at an efficient operating point. The TTS additionally adopts the threshold-changing mechanism to operate the HEV in a charge-sustaining manner. To show its effectiveness, the TTS is implemented to a through-the-road (TTR) HEV and benchmarked against two conventional control strategies: the dynamic programming (DP) and the EACS. In addition, to facilitate real-time application, an adaptive version of the TTS is also developed, which updates the parameters in TTS online by using pattern recognition techniques with a feedback controller.