A Scenario-Based Hardware-in-the-Loop Platform for Real-Time Road-Load Emulation on Production Micromobility Drives

Abstract

Software-defined electric vehicles have reached micromobility, creating a growing need to evaluate how controller software shapes drive performance and energy use. This requires experimental platforms with quantified emulation fidelity and measurement performance. This paper presents a scenario-based hardware-in-the-loop platform combining a production e-scooter drive, a controlled magnetic particle brake, and a real-time road-load model. The platform reproduces rolling resistance, aerodynamic drag, and speed-gated inertial demand for a nominal 90 kg vehicle. Across eight repetitions of a scaled ECE-15 urban cycle, including a cold first run, the protective load cap retained 99.51% of the commanded load impulse. A post hoc sensitivity analysis of the seven warm runs gave 99.71%. Measured torque and speed tracking root-mean-square errors over all eight runs were 0.704 N·m and 0.593 km/h. Separate electrical characterization produced a machine efficiency map peaking at 86.3% and cycle-energy measurements with a coefficient of variation of 0.72%. Subsampling unfiltered 200 kHz recordings at every sampling offset gave a maximum absolute cycle-energy error of 0.14% at 2 kHz, a hundredfold reduction in retained samples under the tested conditions. These results provide a quantified experimental basis for micromobility drive testing and subsequent controller-software comparisons.