Estimation of Remaining Mileage for Pure Electric Vehicle Based on Condition Identification and Prediction

LI Fangzhou; ZHONG Yong; QIU Huangle; FAN Zhouhui; LI Shaowei

doi:10.3969/j.issn.1001-2222.2024.05.012

Vehicle Engine ›› 2024, Vol. 0 ›› Issue (5) : 86. DOI: 10.3969/j.issn.1001-2222.2024.05.012

Estimation of Remaining Mileage for Pure Electric Vehicle Based on Condition Identification and Prediction

LI Fangzhou,ZHONG Yong,QIU Huangle,FAN Zhouhui,LI Shaowei

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Abstract

To enhance the accuracy of remaining mileage estimation method for pure electric vehicles, a novel model centered on the identification and prediction of vehicle driving conditions was put forward. By gathering real-world vehicle driving condition data, the techniques such as fuzzy clustering were used to discern and analyze condition states. Furthermore, a fuzzy rule base correlating vehicle energy consumption with condition-specific parameters was established. Concurrently, the Hidden Markov model was employed to forecast driving conditions. By combining condition identification and prediction, a methodology for estimating the remaining mileage of pure electric vehicles was developed. During the simulation of entire vehicle remaining mileage in AVL CRUISE, the hybrid working conditions which integrate CLTC and WLTC were used to closely mimic real-world driving conditions. Two estimation methods of condition identification alone and condition identification with prediction were compared in detail. The results reveal that the estimation error increases gradually with the increase of time based on the identification of working conditions, and decreases effectively after the introduction of working condition prediction method. Specifically, the maximum absolute error and mean absolute error for the condition identification and prediction methods reduce by 34.04% and 55.79% respectively. Moreover, the standard deviation decreases to 1.44 km. These results prove the superior accuracy of the proposed method, which presents a new perspective on forecasting the range of pure electric vehicles.

Key words

pure electric vehicle / remaining mileage / estimation / fuzzy clustering / Hidden Markov model

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LI Fangzhou,ZHONG Yong,QIU Huangle,FAN Zhouhui,LI Shaowei. Estimation of Remaining Mileage for Pure Electric Vehicle Based on Condition Identification and Prediction[J]. Vehicle Engine. 2024, 0(5): 86 https://doi.org/10.3969/j.issn.1001-2222.2024.05.012