Energy Consumption Simulation and Parameter Optimization of Electric Commercial Vehicles Based on Real-world Driving Cycle

With the increasing trend of commercial vehicle electrification, studying the impact of vehicle parameter optimization on energy consumption and formulating a parameter optimization scheme to reduce energy consumption and improve driving range have become important for the future development of electric vehicles. In this study, a real-world driving cycle was developed using the micro-trip method. Then, within the design optimization range, a vehicle energy consumption simulation under the real-world driving cycle was carried out in ADVISOR with five vehicle parameters (e.g., vehicle mass, rolling resistance coefficient, and accessory power) as variables. Based on the simulation output, the numerical relationships between parameters and energy consumption per 100 km were analyzed under real-world driving cycle. The relationship between the optimization percentage of each parameter and the energy saving per 100 km was analyzed, and the electricity-saving coefficient was established to reflect the energy consumption sensitivity of each parameter. Based on the results of the sensitivity analysis, parameter optimization schemes were developed for vehicle parameters with high expected benefits, and their corresponding cost-benefit analyses were conducted. The results indicate that compared with the New European Driving Cycle (NEDC), the relative error between the energy consumption simulation under the real-world driving cycle and the actual energy consumption is reduced by more than 10%. The vehicle parameters could be sorted in following order (from high to low) according to energy consumption sensitivity: vehicle mass, transmission efficiency, rolling resistance coefficient, aerodynamic drag coefficient, and accessory power. Among the parameter optimization schemes, using aluminum body-in-white material, equipping low rolling resistance tires, and using heat pump air conditioners have positive static benefits. The results indicate that the energy consumption simulation under the real-world driving cycle replicated the actual energy consumption of the target vehicle with a rather good accuracy, and the simulation-based energy consumption sensitivity analysis and parameter optimization have practical guidance significance. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.