A Model-Based EV Driving Range Assessment with Genetic-Algorithm-Optimized Motor Waste Heat Recovery Strategies
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PUBLIC SUMMARY
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A plug-and-play vehicle-thermal co-simulation platform assesses TMS impacts.
TMS (Thermal Management System) cuts EV range 12–16% in summer, 25–31% in winter.
Cabin shell heat load dominates year-round; >80% in winter drives heat pump use.
Range varies near-linearly with ambient, occupants, absorptivity, transmittivity.
WHR (Waste Heat Recovery) saves more in steady state; S1 outperforms S2; GA guides tuning.
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ABSTRACT
This study develops a coupled vehicle-thermal management simulation platform integrating FASTSim dynamics, reduced-order thermal models, and an R134a air-source heat pump (ASHP) to evaluate the impact of thermal management system (TMS) on EV energy consumption and optimize motor waste heat recovery (WHR) in winter. Simulation results under the WLTP cycle show that TMS activation reduces driving range by 12% to 16% in summer and 25% to 31% in winter, with cabin envelope heat load being the dominant factor (＞80% in winter) and ambient temperature the most influential external parameter. Three heating modes are compared: S0 (pure ASHP), S1 (on-off WHR controlled by Ton/Toff), and S2 (dual-source WHR regulated by Qwhr). Using genetic algorithm (GA) to minimize average TMS power under hard constraints, optimal S1 and S2 strategies at −5°C reduce heat pump energy consumption (excluding battery PTC) by 16% and 9% respectively versus S0, corresponding to range gains of 1.8% and 1.0%. Immediate heat recovery after cold start is suboptimal; S1 requires delayed activation with sufficient hysteresis, while S2 exhibits a clear Qwhr trade-off. Overall winter energy savings are constrained by dominant battery PTC consumption during warm-up, becoming more significant during steady-state operation. These findings provide quantitative insights for WHR parameter tuning and strategy mapping based on operational conditions. -
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Zhao L., Mohebi P. and Wang Z. (2025). A Model-Based EV Driving Range Assessment with Genetic-Algorithm-Optimized Motor Waste Heat Recovery Strategies. Energy Use 1:100005. https://doi.org/10.59717/ipj.energy-use.2025.100005
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Zhao L., Mohebi P. and Wang Z. (2025). A Model-Based EV Driving Range Assessment with Genetic-Algorithm-Optimized Motor Waste Heat Recovery Strategies. Energy Use 1:100005. https://doi.org/10.59717/ipj.energy-use.2025.100005
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Figure 1.
Overview of cabin thermal model.
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Figure 2.
Cabin model validation.
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Figure 3.
Temperature simulation results.
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Figure 4.
Thermal load.
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Figure 5.
System power simulation results.
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Figure 6.
Sensitivity analysis of total power consumption, thermal load and driving mileage in summer and winter.
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Figure 7.
Optimized WHR model.