Research on Energy Consumption Evaluation of Electric Vehicle Considering Air Conditioning Energy Consumption
Ning Li, Yingshuai Liu, Junzhi Zhang, Chao Li, Yuan Ji, Weilong Liu · 2022 · 0 citationsRead the paper
Abstract This article discusses how to accurately evaluate the whole vehicle energy consumption under different refrigeration and heating working states of electric vehicles. Firstly, using the actual driving test data of electric vehicle, the weight coefficients of electric vehicle under refrigeration, heating and uncooled heating were obtained by algorithm. Then, the above weight coefficient was combined with the drum test results to obtain the annual comprehensive 100km energy consumption value of the vehicle, at the same time, the comprehensive energy consumption value of 100km of the vehicle under different comfort control modes of electric vehicle was analyzed. The related vehicle tests were carried out, the simulation and experimental results showed that the weight coefficient obtained by the least square method can better reflect the real energy consumption of the whole vehicle, the evaluation method of 100km energy consumption of electric vehicle proposed in this paper is a feasible evaluation method.
What the full text shows
Working prototype- The least square method for calculating weight coefficients provides a more accurate reflection of real energy consumption than the time-based weight coefficient method. — 14.35% to 14.62% lower annual energy consumption calculation vs. time-based method (NEDC and CLTC-P working conditions)
- Annual 100km energy consumption varies by thermal comfort control mode, with the highest consumption in comfort mode and lowest in power saving mode. (Across NEDC and CLTC-P cycles)
- The energy consumption calculated via the least square method shows high alignment with simulation results. — Error within ±5% (specifically 0.80% increase for NEDC and 1.90% increase for CLTC-P vs. simulation) (Annual 100km energy consumption)
- Setup
- Electric vehicle tested using NEDC and CLTC-P cycles on a ROADSIM 48” 4xType4 chassis dynamometer in an environmental simulation and emission test room.
- How
- The researchers used a least square method algorithm on actual driving data to determine weight coefficients for refrigeration, heating, and uncooled states. These coefficients were combined with chassis dynamometer (drum) test results to calculate annual comprehensive 100km energy consumption across different comfort control modes.
- Limitations
- Test results are subject to fluctuations due to environmental, equipment, and human factors. · Heating tests used relatively low target temperatures due to the slow heating speed of electric vehicles.
Summarized by Gemma 4 from the open-access full text · 9 Oct 2026. Read it