Fault Detection and Failure Rate Analysis of New Energy Vehicles Based on Decision Tree Algorithm

[1] Liu, Z., Hao, H., Cheng, X., & Zhao, F. (2018). Critical issues of energy efficient and new energy vehicles development in china. Energy Policy, 115(APR.), 92-97. Search in Google Scholar

[2] Wang, Z., Zhao, C., Yin, J., & Zhang, B. (2017). Purchasing intentions of chinese citizens on new energy vehicles: how should one respond to current preferential policy?. Journal of Cleaner Production, 161(sep.10), 1000-1010. Search in Google Scholar

[3] Jia, S., & Wu, B. (2018). Incorporating lda based text mining method to explore new energy vehicles in china. IEEE Access, PP(99), 1-1. Search in Google Scholar

[4] Mao, J., Hong, D., Ren, R., Li, X., & Nasr, E. S. A. (2020). Driving conditions of new energy logistics vehicles using big data technology. IEEE Access, PP(99), 1-1. Search in Google Scholar

[5] Luo, C., Shen, Z., Evangelou, S., Xiong, G., & Wang, F. Y. (2019). The combination of two control strategies for series hybrid electric vehicles. IEEE/CAA Journal of Automatica Sinica, 6(2), 596-608. Search in Google Scholar

[6] Chen, K., Zhao, F., Hao, H., & Liu, Z. (2019). Selection of lithium-ion battery technologies for electric vehicles under china’s new energy vehicle credit regulation. Energy Procedia, 158, 3038-3044. Search in Google Scholar

[7] Zeng, X., Sun, X., & Zhao, F. (2022). Energy-saving intelligent manufacturing optimization scheme for new energy vehicles. International journal of emerging electric power systems. Search in Google Scholar

[8] Kilic, A., & Weiss, F. (2023). Early detection of pmsm faults at static and dynamic operating points by using artificial neural network for automated electric vehicle. Journal of the Brazilian Society of Mechanical Sciences and Engineering(9), 45. Search in Google Scholar

[9] Song, R., & Li, B. (2021). Surrounding vehicles’ lane change maneuver prediction and detection for intelligent vehicles: a comprehensive review. IEEE Transactions on Intelligent Transportation Systems, PP(99), 1-17. Search in Google Scholar

[10] Kang, Y., Duan, B., Zhou, Z., Shang, Y., & Zhang, C. (2020). Online multi-fault detection and diagnosis for battery packs in electric vehicles. Applied Energy, 259(Feb.1), 114170.1-114170.16. Search in Google Scholar

[11] Zhang, J., Salman, M., Zanardelli, W., Ballal, S., & Cao, B. (2020). An integrated fault isolation and prognosis method for electric drive systems of battery electric vehicles. IEEE Transactions on Transportation Electrification, PP(99), 1-1. Search in Google Scholar

[12] A, S. S. M., B, A. K., & B, H. A. (2019). A comparison of various open-circuit fault detection methods in the igbt-based dc/ac inverter used in electric vehicle - sciencedirect. Engineering Failure Analysis, 96, 223-235. Search in Google Scholar

[13] Wyk, F. V., Wang, Y., Khojandi, A., & Masoud, N. (2019). Real-time sensor anomaly detection and identification in automated vehicles. IEEE Transactions on Intelligent Transportation Systems. Search in Google Scholar

[14] Bijjahalli, S., & Sabatini, R. (2019). A high-integrity and low-cost navigation system for autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems, PP(99), 1-14. Search in Google Scholar

[15] Zhang, H., & Wang, J. (2017). Active steering actuator fault detection for an automatically-steered electric ground vehicle. Vehicular Technology, IEEE Transactions on, 66(5), 3685-3702. Search in Google Scholar

[16] Zhang, J., Yao, H., & Rizzoni, G. (2017). Fault diagnosis for electric drive systems of electrified vehicles based on structural analysis. IEEE Transactions on Vehicular Technology, 66(2), 1027-1039. Search in Google Scholar

[17] Choudhary, A., Fatima, S., & Panigrahi, B. K. (2023). State-of-the-art technologies in fault diagnosis of electric vehicles: a component-based review. IEEE transactions on transportation electrification(2), 9. Search in Google Scholar

[18] Eldeeb, H. H., Zhao, H., & Mohammed, O. A. (2020). Detection of ttf in induction motor vector drives for ev applications via ostu’s-based ddwe. IEEE Transactions on Transportation Electrification, PP(99). Search in Google Scholar

[19] Obeid, N. H., Battiston, A., Boileau, T., & Nahid-Mobarakeh, B. (2017). Early intermittent interturn fault detection and localization for a permanent magnet synchronous motor of electrical vehicles using wavelet transform. IEEE Transactions on Transportation Electrification, PP(3), 1-1. Search in Google Scholar

[20] Qin, L., He, X., Yan, R., Deng, R., & Zhou, D. (2017). Distributed sensor fault diagnosis for a formation of multi-vehicle systems. Journal of the Franklin Institute, 356(2), 791-818. Search in Google Scholar

[21] Abassi, M., Khlaief, O., Saadaoui, O., Chaari, A., & Boussak, M. (2017). Real-time implementation of discrete fourier transform phase analysis and fault tolerant control for pmsm in electric vehicles. COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. Search in Google Scholar