A Minimally Intrusive Methodology for Power Loss Identification in Electric Powertrains for Physics-Based Analytical Modeling

This paper presents a minimally intrusive experimental methodology for identifying and modeling power losses in the electric powertrain of a battery electric vehicle, including the inverter, electric motor and speed reducer. Measurements are performed on a roller test bench equipped with an eddy current brake, using two complementary approaches to determine the mechanical power at the wheel: (i) a direct measurement based on an onboard rotary torque sensor integrated into a driveshaft; (ii) an indirect estimation derived from brake power measurements corrected for bench losses and tire longitudinal slip. The two approaches are systematically compared in order to quantify the accuracy loss associated with brake-based measurements and to identify the operating conditions under which they can reliably substitute direct torque measurements. The experimental results show that brake-based estimations provide acceptable accuracy at moderate–high torque levels, while significant deviations occur at low torque. Based on the experimental dataset, an overall power loss model is identified using a polynomial function of motor torque and speed. Two fitting strategies are investigated: an unconstrained least-squares approach, allowing all coefficients to vary freely, and a constrained formulation enforcing physically admissible (non-negative) loss terms; while the unconstrained method slightly improves the numerical fit, it may lead to non-physical coefficients and invalid efficiency predictions. In contrast, the constrained approach preserves physical interpretability and ensures consistent loss and efficiency maps. Finally, a step-by-step practical guide is provided to facilitate the implementation of the proposed methodology for powertrain loss identification on electric vehicles without extensive mechanical disassembly.