Structural improvement and segmented model predictive control strategy for engine–battery coupled thermal management system under low-temperature conditions

To address the challenges of low efficiency and insufficient control precision in the engine–battery coupled thermal management system (CTMS) of hybrid electric vehicles (HEVs) under low-temperature conditions, this study proposes a high-efficiency coordinated thermal management strategy. First, an improved CTMS structure is developed to enhance residual heat utilization, and its battery preheating efficiency under different ambient temperatures is comparatively analyzed against that of the conventional structure based on the rule-based control strategy. Second, for the improved engine-battery CTMS, a multivariable segmented model predictive control (MPC) incorporating dynamic weight adjustment is designed to enhance control accuracy and energy utilization efficiency further. Simulation results demonstrate that the improved system structure reduces the time required to preheat the battery from – 20 °C ∼ −5 °C to 25 °C by more than 61% and 50% under the FTP-75 and WLTC driving cycles, respectively. Moreover, compared with the rule-based control strategy, the segmented MPC strategy achieves accurate regulation of both engine coolant and battery temperature, with relative errors maintained within 1%, while substantially mitigating high-frequency oscillations of actuators. The proposed system structure and control strategy thus provide a theoretically sound and practically feasible solution for efficient thermal management of HEVs operating in low-temperature conditions.