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AI and ML Powered IoT Applications for Energy Management in Electric Vehicles

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Abstract

The advantages of real-time dataset with artificial intelligence-based machine learning algorithms can be utilized for improving energy management in Electric Vehicles (E-Vehicle). Here the machine learning algorithms such as classification, regression, reinforcement, and clustering are incorporated to identify the suitable profile pattern. Electric vehicle modelling can be developed from profile, outline, and formulation for energy efficiency can be done from vehicle state, specifications from acceleration and deceleration with necessary constraints. Each vehicle energy management stages are realized as kinetic energy, mechanical energy, and electrical energy for minimizing the losses within a boundary except proving the constraints. With a problem formulated in each stage for classifying the input profile, it is found that regression analysis matches the energy optimization, reinforcement technique fixes the boundary at every profile input and clustering of data ensures formation of data set. The proposed scheme is validated with MATLAB/Simulink environment and the results shows that the new methods improved the energy efficiency in every stage at the level of 10 to 30%. Also, among the energy efficient techniques, classification and regression schemes adds an error loss of 0.2 to 0.3%, the reinforcement method includes the data handling error of 0.3 to 0.4% and finally, the clustering method increases the error loss in the level of 0.4 to 0.5%.

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Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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This research work has not received any funding from any organization.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India

    M. Mathankumar

  2. Department of Electrical and Electronics Engineering, New Horizon College of Engineering, Bengaluru, India

    B. Gunapriya & A. Singaravelan

  3. Department of Computer Science and Business Systems, M Kumarasamy College of Engineering, Karur, India

    R. Raja Guru

  4. CTiF Global Capsule, Department of Business Development and Technology, Aarhus University, Herning, Denmark

    P. Sanjeevikumar

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  1. M. Mathankumar
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  2. B. Gunapriya
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  3. R. Raja Guru
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  4. A. Singaravelan
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  5. P. Sanjeevikumar
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Correspondence to M. Mathankumar.

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Mathankumar, M., Gunapriya, B., Guru, R.R. et al. AI and ML Powered IoT Applications for Energy Management in Electric Vehicles. Wireless Pers Commun 126, 1223–1239 (2022). https://doi.org/10.1007/s11277-022-09789-6

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  • DOI: https://doi.org/10.1007/s11277-022-09789-6

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