Integrating Gear Shifting Preference into Personalized Shift-Scheduling Calibration

Shift-scheduling calibration of automatic transmission (AT) vehicles is vital for both driving experience and automobile industry. Shifting schedules are usually calibrated with the consideration fuel economy drivability while neglecting individual preference. In this work, we propose to exemplify shifting preference by integrating manual (MT) habit into AT shift-scheduling calibration, where reflected as points available in most automated (AMT) vehicles. The directed using particle swarm optimization (PSO), during virtual cycle test, i.e., FTP-72. Candidate shifting-schedules generated overlapped zone MT space around base map, evaluated on quality economy. Through iterations, candidate shift tested assessed until overall performance reach optimum. Experimental results presented show effectiveness proposed method, which retains preferences well enhances index about 5%, 4%, 2% drivers aggressive, moderate, mild styles, respectively.