Thermal-energy co-optimization management strategy based on specific heat generation rate

Electrifying series hybrid electric vehicle (SHEV) powertrains enhances fuel economy and power density but poses control challenges due to extreme thermal loads on high-power-density (HPD) engines, constrained compartment space, complex heat dissipation requirements, and dynamic energy allocation demands. A novel nonlinear model predictive control (NMPC) framework with integrated thermal management is proposed to synergistically optimize economic performance and low heat generation demands. To characterize the thermal-to-energy conversion efficiency of HPD engines, the specific heat generation rate (SHGR, defined as heat generation per unit power output) is introduced as a key metric. A mapping model correlating optimal SHGR with speed-torque operating conditions is established, thereby formulating a dual-objective optimization strategy for fuel economy and thermal management. The proposed dynamic engine operating-point adjustment strategy enables Thermal-Energy Co-Optimization (TECO) under the constraints of battery state of charge (SOC) retention and dynamic performance requirements. Simulations and hardware-in-the-loop (HIL) experiments demonstrate that, compared to conventional rule-based strategies, the proposed approach reduces engine heat generation by 3.11 % and the fuel consumption rate by 7.06 % under typical operating conditions without compromising power output. In off-road scenarios, the optimization effects are further amplified, with 10.2 % and 11.3 % reductions in engine heat generation and fuel consumption, respectively, significantly enhancing comprehensive energy efficiency.