Adaptive Energy Management Strategy for Extended-Range Electric Vehicle Based on Micro-Trip Identification

In order to improve the fuel economy of an extended-range electric vehicle with the engine-generator, an adaptive energy management strategy has been proposed in this paper. First, micro-trip decomposition analysis of the standard driving cycles are conducted, and these micro trips are classified as four kinds of driving patterns by K-means clustering method. Second, an optimal energy allocation for the engine-generator and battery is designed by Pontryagin's minimum principle (PMP). The proposed approach should realize the energy management and maintain the battery in a charge sustaining mode. Third, an online optimal control is conducted by a micro-trip identification algorithm. By utilizing the clustering driving patterns, the adaptive energy management strategy is achieved by the selection of optimal PMP co-state variable. Finally, the experimental performance comparisons for different control strategies and driving cycles are investigated to shown the efficiency of proposed controller.