Predictive cruise control for 4WD electric vehicle based on dynamic weight factors. (November 2022)

• Record Type: Journal Article
• Authors: Wu, Dongmei; Yuan, Quan; Du, Changqing; Yan, Fuwu; Li, Yang
• Is Part Of: Energy reports. Volume 8(2022)Supplement 15
• Page Start: 237
• Page End: 246
• Publication Date: 2022-11
• Subjects: Predictive cruise control -- Energy saving -- Dynamic weight factors -- MPC -- 4WD electric vehicle; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2022.10.097
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: By computing the velocity trajectory based on the advancing road and traffic information, the predictive cruise control (PCC) system can significantly reduce vehicle energy consumption. As the weight factors of different objective item have an important influence on the control results of PCC system, this paper proposed a novel optimization method with dynamic weight factors according to the classification of road slope for 4 wheel drive intelligent (4WD) electric vehicles. In order to determine the weight coefficient adjustment method, the influence of road slope on the PCC performance was analyzed and a road category identification method was presented. The results of simulation indicated that the proposed PCC based on dynamic weight coefficients can improve the adaptability of PCC on different categories of road. Compared with the traditional PCC with constant weight coefficient, the maximum energy-saving rate can reach 32.3% at a small cost of driving distance 3.86% on rapid downhill road. For other type of road, uphill and continuously undulating road, the energy-saving rate was low, where it was more important to improve the driving efficiency by 1.46%.