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  11. Dynamic Solar Irradiance Estimation For Vehicle Thermal Management Using A Multi-modal Machine Learning Framework

Dynamic solar irradiance estimation for vehicle thermal management using a multi-modal machine learning framework

Rial A Rajagukguk1, Hoseong Lee2, Hyunjin Lee3

  • 1Department of Mechanical Engineering, Kookmin University, Seoul, 02707, Republic of Korea.

Scientific Reports
|December 8, 2025

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View abstract on PubMed

Summary
This summary is machine-generated.

Accurate solar irradiance estimation for moving vehicles is now possible with a new machine learning framework. This technology enhances thermal management and energy efficiency in electric vehicles (EVs).

Area of Science:

  • Environmental Science
  • Automotive Engineering
  • Data Science

Background:

  • Accurate solar irradiance estimation is crucial for vehicle thermal management, especially for electric vehicles (EVs) where it impacts battery life and range.
  • Existing methods struggle with dynamic conditions during vehicle movement, limiting real-world applicability.

Purpose of the Study:

  • To develop a novel machine learning framework for real-time solar irradiance estimation around moving vehicles.
  • To improve thermal management and energy optimization strategies in vehicles.

Main Methods:

  • Integration of satellite remote sensing and sky camera imagery.
  • Validation using field data from an instrumented vehicle with sensors (solar irradiance, GPS, environmental).
  • Fusion of multi-source environmental data for high spatiotemporal resolution predictions.
Keywords:
Machine learningMoving vehiclesSatellite dataSky images

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Main Results:

  • The framework achieved strong performance with normalized root-mean-square errors of 14.61% in summer and 17.10% in winter.
  • High spatiotemporal resolution predictions of solar irradiance under diverse conditions were delivered.
  • The model demonstrated effectiveness across various routes and seasonal conditions.

Conclusions:

  • The proposed framework provides accurate, real-time solar irradiance estimates for moving vehicles.
  • Enables adaptive, location-aware thermal management strategies for enhanced energy efficiency and passenger comfort.
  • The integration of satellite and ground-based data ensures scalability for various regions and vehicle types.
Solar irradiance