Abstract
Even though heavy-commercial vehicles have a relatively low population density (11%), they still account for a large share of urban noise and CO2 emission (37%). Therefore, trucks are a priority for full electrification. However, heavy-duty trucks (HDT) have complex array of challenges: high energy consumption combined with high daily driving distances. This paper investigates the effect of operating temperature on HDT energy performance. A high-fidelity multi-physics model of electric machine with fixed and variable parameters as nonlinear functions of temperature and coolant flow characteristics was developed. Temperature-dependent motor maps were then generated and integrated with forward-facing vehicle model. Quantitative analyses under different operating conditions with a realistic cycle (ESK) have shown that temperature plays a crucial role for the energy efficiency of EVs.
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