An Adaptive Energy Management Strategy for Extended-Range Electric Vehicles Based on Pontryagin's Minimum Principle

Hybrid Electric Vehicles (HEVs) have become a mature technology for saving fuel and solving environmental problems. Fuel consumption in HEVs depends heavily on the control concept that distributes power among the power sources and manages the State of Charge (SOC) of the battery. Optimal control strategies based on the Equivalent Consumption Minimization Strategy have been thoroughly studied previously, and prior results show that the control strategies achieved high fuel efficiencies. However, predictions of driving patterns are required in order to implement the optimal control concept. Furthermore, obtaining driving patterns is very difficult because various driving situations should be considered when evaluating the equivalent fuel consumption of an HEV. Thus, the optimal control is difficult to implement in real-world applications. In this paper, an adaptive optimal control strategy based on Pontryagin''s Minimum Principle is introduced, which can be applied to real vehicles and does not require forecasting of driving patterns. Instead, it uses an adaptive concept for balancing the SOC. The performance of the control concept is evaluated in simulations for GM Volt 1st Gen, and the results show approximately 9.16% improvement in fuel consumption compared to other control concepts.