Multi-objective parameter optimization strategy based on engine coordinated control for improving shifting quality

In order to address the poor shifting quality issue of a certain model of heavy-duty vehicles, a multi-objective parameter optimization strategy based on engine coordinated control is proposed. This strategy aims to improve shifting quality by reducing the sliding friction work and impact during the shifting process. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is employed to perform multi-objective optimization on the coordinated control parameters, which include external control torque of the engine, start of fuel cut-off timing, and duration of fuel cut-off. By comparing the performance of different parameter combinations in terms of sliding friction work and impact, the optimal parameter combination is determined. Through bench testing verification, it has been demonstrated that utilizing the optimized parameters for engine coordinated control during the torque phase of the shifting process can significantly enhance shifting quality. This strategy provides an effective solution for addressing shifting quality issues.