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One of the main components in electric vehicles that influences the performance of the electric vehicle is the lithium-ion battery used. Frequent health monitoring of the EV battery by diagnosing the faults is essential for the durability and safety of the vehicle. Nowadays, many deep learning models are developed to monitor the health of battery-based fault diagnosis. However, in order to train and test these deep learning models large amount of data is required. In this chapter, the complete procedure to develop an EV battery faults dataset using MATLAB is presented. Also, all the data analytics of the developed EV battery faults dataset are presented in this chapter. The data presented in this paper can be useful to researchers who are working on applications of artificial intelligence in electric vehicles. In this chapter, data generation based on short-circuit faults in EV batteries, over-discharge faults, and healthy conditions is discussed. Two datasets are created using MATLAB, and those datasets are the Electric Vehicle Battery Health Simple Classification (EVBHSC) dataset and the Electric Vehicle Battery Health Multiple Classification (EVBHMC) dataset.

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Development of Dataset to Diagnose Electric Vehicle Battery Faults Using Deep Learning Techniques

  • 章节

  • 发表日期：

    2025年

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  • Venkataramana Veeramsetty,
  • Janagani Sai Varshith,
  • Prathapagiri Pragnia,
  • Manmadha Kumar Boddepalli,
  • Surender Reddy Salkuti

摘要

One of the main components in electric vehicles that influences the performance of the electric vehicle is the lithium-ion battery used. Frequent health monitoring of the EV battery by diagnosing the faults is essential for the durability and safety of the vehicle. Nowadays, many deep learning models are developed to monitor the health of battery-based fault diagnosis. However, in order to train and test these deep learning models large amount of data is required. In this chapter, the complete procedure to develop an EV battery faults dataset using MATLAB is presented. Also, all the data analytics of the developed EV battery faults dataset are presented in this chapter. The data presented in this paper can be useful to researchers who are working on applications of artificial intelligence in electric vehicles. In this chapter, data generation based on short-circuit faults in EV batteries, over-discharge faults, and healthy conditions is discussed. Two datasets are created using MATLAB, and those datasets are the Electric Vehicle Battery Health Simple Classification (EVBHSC) dataset and the Electric Vehicle Battery Health Multiple Classification (EVBHMC) dataset.