Optimizing Energy Recovery in Hybrid Electric Vehicles Using A-ECMS Strategy

The fuel efficiency of plug-in hybrid electric vehicles (PHEVs) is largely influenced by their energy management strategies. This paper presents, for the first time, a dual static adaptive A-ECMS (Adaptive Equivalent Consumption Minimization Strategy) energy management controller designed to address energy management challenges in dual-motor PHEVs. The robustness of this controller was also evaluated under perturbations. A-ECMS (Adaptive Equivalent Consumption Minimization Strategy) is an advanced real-time control strategy for energy management in plug-in hybrid electric vehicles (PHEVs). Building upon the classic ECMS (Equivalent Consumption Minimization Strategy), it enhances adaptability and efficiency by dynamically adjusting to varying driving conditions, ensuring optimal fuel consumption and battery utilization. In the experiments, the performance of the A-ECMS strategy was compared against the ECMS strategy and the RB (Rule-Based) strategy, the latter serving as an ideal optimization benchmark. Additionally, we analyzed the equivalent factors of A-ECMS and examined the impact of initial equivalent factors on the experimental outcomes. The results demonstrated that, compared to the ECMS strategy, the A-ECMS approach enhanced fuel economy by 7.8% and reduced CO2 emissions by 15.14 g/km. To further assess the robustness of this method, 5% random noise was introduced into typical operating conditions. Even under these conditions, the A-ECMS strategy still achieved a 6.9% improvement in fuel economy and a 14.39% reduction in CO2 emissions compared to the ECMS strategy. From an economic perspective, the proposed A-ECMS strategy led to cost savings of 30.17% and 28.56% in two different scenarios relative to the ECMS strategy. These findings highlight the effectiveness of the A-ECMS strategy in enhancing fuel efficiency, reducing CO2 emissions, and lowering operational costs for PHEVs. This study provides valuable insights for future research in energy management strategies for hybrid electric vehicles.