Trip energy consumption estimation for electric buses

This study aims to develop a trip energy consumption (TEC) estimation model for the electric bus (EB) fleet planning, operation, and life-cycle assessment. Leveraging the vast variations of temperature in Jilin Province, China, real-world data of 31 EBs operating in 14 months were collected with temperatures fluctuating from -27.0 to 35.0 & DEG;C. TEC of an EB was divided into two parts, which are the energy required by the traction and battery thermal management system, and the energy required by the air conditioner (AC) system operation, respectively. The former was regressed by a logarithmic linear model with ambient temperature, curb weight, travel distance, and trip travel time as contributing factors. The optimum working temperature and regression parameters were obtained by combining Fibonacci and Weighted Least Square. The latter was estimated by the operation time of the AC system in cooling mode or heating mode. Model evaluation and sensitivity analysis were conducted. The results show that: (i) the mean absolute percentage error (MAPE) of the proposed model is 12.108%; (ii) the estimation accuracy of the model has a probability of 99.7814% meeting the requirements of EB fleet scheduling; (iii) the MAPE has a 1.746% reduction if considering passengers' boarding and alighting.

Automated summary

This study developed a trip energy consumption estimation model for electric bus fleet planning, operation, and life-cycle assessment. Real-world data from 31 electric buses operating in Jilin Province, China were collected to consider the effects of temperature variations. The model accurately estimated the energy consumption of the traction and battery thermal management system, as well as the air conditioner system, demonstrating its usefulness for fleet scheduling.