ABSTRACT
Hybrid powertrain technology is an effective solution for energy-saving and carbon emission reduction in commercial vehicles. The research and development focus of hybrid powertrain systems has shifted from optimizing engine performance to maximizing system efficiency. This paper aims to investigate the energy management strategy (EMS) design and optimization of a hybrid powertrain system for an 18-ton intercity logistics vehicle. Based on the World Harmonized Heavy-Duty Vehicles Test Cycle (C-WTVC), a multi-objective optimization approach is employed. Firstly, a power split hybrid powertrain system model is established, and a system cost model is developed that includes equivalent fuel consumption, battery state of charge deviation, and battery aging. The dynamic programming (DP) global optimization strategy is then applied using the cost function as the optimization objective. The Pareto optimal algorithm is utilized, and the Analytic Hierarchy Process (AHP) is employed to determine the multi-objective optimal solution along the Pareto front. Based on the optimal solution data, Gaussian Support Vector Machine (SVM) is employed for pattern recognition, and the Equivalent Fuel Consumption Minimization Strategy (ECMS) power allocation strategy is established with equivalent fuel consumption and battery aging as the objective functions. A comparison with rule-based strategies shows that the proposed strategy reduces fuel consumption costs by 9.5%, battery aging costs by 4.3%, and overall costs by 6%. This strategy effectively balances fuel consumption and battery aging, resulting in a significant reduction in overall system costs.
