Multi-objective optimization energy management strategy for hybrid heavy-duty vehicles equipped with dual auxiliary power units considering battery aging and cabin comfort adjustment

Operating temperature strongly influences the performance and durability of lithium-ion batteries (LIBs) in hybrid heavy-duty vehicles equipped with dual-auxiliary power units (APUs). However, existing energy management strategies (EMSs) often insufficiently consider the coupled electro–thermal behavior of the battery, the high energy demand of cabin heating, ventilation, and air conditioning (HVAC) systems, and the coordination complexity of dual-APU architectures, resulting in suboptimal energy allocation and degraded lifecycle performance. This paper proposes a thermal- and health-aware EMS based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The proposed strategy simultaneously regulates the thermal states of the LIB while adaptively managing cabin HVAC loads, enabling coordinated optimization of energy efficiency, battery health, and passenger comfort. An integrated energy–thermal co-optimization framework is established by coupling an electro–thermal battery degradation model, a cabin–HVAC thermal load model, and a battery thermal management model. Fuel consumption, battery degradation, HVAC energy use, and state-of-charge imbalance are jointly considered in the optimization process. Simulation results demonstrate that the proposed EMS reduces the equivalent fuel consumption by 3.50%, 1.78%, and 5.57%, respectively, compared with conventional TD3-based energy management strategies. Moreover, it attains the highest final state of health (SOH) and effective cabin thermal regulation, which effectively suppresses the battery aging rate and demonstrates considerable potential for enhancing the long-term durability of the system.