A Comparative study of Different Hybrid Electric Powertrain Architectures for Heavy-Duty Truck. Issue 31 (2018)

• Record Type: Journal Article
• Authors: Xu, Chao; Guo, Kunfang; Yang, Fuyuan
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 31(2018)
• Page Start: 746
• Page End: 753
• Publication Date: 2018
• Subjects: Hybrid heavy-duty truck -- Total cost of ownership -- Battery degradation -- Optimal sizing -- Dynamic programming; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.10.136
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In this paper, three different hybrid electric powertrain architectures are compared based on a heavy-duty truck running the Chinese-World Transient Vehicle Cycle (C-WTVC). The fuel consumption and battery costs of the different architectures are optimized by using the dynamic programming (DP) approach, based on a dynamic degradation model of the LiFePO4 battery. Based on the DP results, near-optimal rule-based control strategies of different powertrains for on-line uses are proposed. Finally, the three architectures are comprehensively compared from different aspects, including fuel economy, initial cost, and payback period in the total cost of ownership. Simulation results show that all architectures have their merits and drawbacks, and can be used in different applications to meet different requirements. In addition, more than 18% fuel economy improvement is achieved when compared to the traditional heavy-duty truck. Under economic scenarios assumptions made, the payback period for hybrid electric heavy-duty trucks are less than six years for the C-WTVC. When economic scenarios assumptions are beneficial toward electrification of vehicles, the shortest payback period will be only three years.