To address the limitations of high costs and prolonged testing cycles associated with traditional real-vehicle evaluation methods for electric vehicle (EV) road condition analysis, a novel forward simulation approach was developed. Based on the longitudinal dynamics theory and the parameters of a specific pure EV, a high-fidelity simulation model was constructed using the MATLAB/Simulink platform. Actual driving cycles were incorporated as input conditions to allow for the systematic evaluation of key power performance indicators, including acceleration capability, maximum gradability, and speed tracking accuracy. It was demonstrated through experimental results that the maximum deviation between simulated values and design targets was merely 3.3%. Through these findings, the model's precision in replicating real-world driving scenarios and its effectiveness in performance assessment were validated. By comparison with conventional testing, development costs can be significantly reduced through the proposed methodology, and a versatile theoretical framework for EV power system optimization can be established. In addition, flexible adaptation to various vehicle configurations and driving environments is enabled by the model’s modular architecture.
Yin et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: