Abstract
Gear shift quality is traditionally optimized in a vehicle on the road, through the evaluation of the driver’s perception. This classical human-feedback-based method faces different challenges, such as low reproducibility and high cost. In order to overcome these drawbacks, an innovative automatic virtual calibration framework is proposed in the Model-in-the-Loop environment. The devised framework is composed of a dynamic model of the transmission system, an adaptive gear shift controller, an objective assessment of the gear shift quality, and a multi-objective optimization algorithm. The Pareto-optimal front with multi-conflicting criteria, such as shift time and shift comfort, can be obtained within this framework. In particular, an improved hybrid multi-objective evolutionary algorithm is developed to enhance the optimization performance. The optimization of the shift trajectory for an automated manual transmission synchronization system is implemented as a case study. The obtained optimal shift trajectories are also validated on a transmission test bench.
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Schedule a callMore From: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
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