THERMAL SCIENCE

International Scientific Journal

RESEARCH ON ENERGY REDISTRIBUTION OF HYBRID VEHICLE CONSIDERING THERMAL CONSTRAINTS

ABSTRACT
Thermal management is one of the key factors affecting the performance of hybrid vehicles. However, most traditional energy management strategies lack the consideration of thermal constraints under harsh operating conditions. In this paper, taking a specific type of diesel-electric hybrid system as the research object, a strategy for energy redistribution under thermal management constraints is proposed. The diesel-electric hybrid system model is built and verified. Based on the model, the cooling capacity indexes are selected, and the weight coefficient of each cooling capacity index is determined by neighborhood component analysis. Then a comprehensive thermal evaluation system is obtained. Combined with the thermal evaluation system, the energy redistribution strategy based on the momentum gradient descent method is proposed. Two typical working conditions of high altitude and battery cooling system deterioration are selected, and the energy redistribution strategy is simulated and analyzed in real-time under both working conditions. The results show that the energy redistribution strategy can significantly improve the thermal state of the system at the expense of less overall energy consumption, take into account the economy and thermal balance, and ensure the reliable operation of the vehicle.
KEYWORDS
PAPER SUBMITTED: 2023-09-22
PAPER REVISED: 2023-10-25
PAPER ACCEPTED: 2023-11-10
PUBLISHED ONLINE: 2024-01-20
DOI REFERENCE: https://doi.org/10.2298/TSCI230922283L
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2024, VOLUME 28, ISSUE Issue 4, PAGES [2845 - 2855]
REFERENCES
  1. Guo, L., et al., Development of Supercapacitor Hybrid Electric Vehicle, Journal of Energy Storage, 65 (2023), 107269
  2. Zhang, Y., et al., Develop of a Fuel Consumption Model for Hybrid Vehicles, Energy Conversion and Management, 207 (2020), 112546
  3. Zhang, S., et al., Modelling and Optimal Control of Energy-Saving-Oriented Automotive Engine Thermal Management System, Thermal Science, 25 (2021), 4B, pp. 2897-2904
  4. Dong, Y., et al., Thermal Protection System and Thermal Management for Combined-Cycle Engine: Review and Prospects, Energies, 12 (2019), 2, 240
  5. Geng, W., et al., A Cascaded Energy Management Optimization Method of Multimode Power-Split Hybrid Electric Vehicles, Energy, 199 (2020), C, 117224
  6. Liu, Y., et al., Energy Management for Hybrid Electric Vehicles Based on Imitation Reinforcement Learning, Energy, 263 (2023), C, 125890
  7. Hu, Q., et al., Multihorizon Model Predictive Control: An Application Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles, IEEE Transactions on Control Systems Technology, 30 (2021), 3, pp. 1052-1064
  8. Alberto, B., et al., Numerical Assessment of Integrated Thermal Management Systems in Electrified Powertrains, Applied Thermal Engineering, 221 (2023), 119822
  9. Wang, X., et al., Energy Management Strategy for Hybrid Electric Vehicle Integrated with Waste Heat Recovery System Based on Deep Reinforcement Learning, SCIENCE CHINA Technological Sciences, 65 (2022), 3, pp. 713-725
  10. Kwon, H., Ivantysynova, M., Experimental and Theoretical Studies on Energy Characteristics of Hydraulic Hybrids for Thermal Management, Energy, 223 (2021), 120033
  11. Jin, L., et al., A Novel Hybrid Thermal Management Approach Towards High-Voltage Battery Pack for Electric Vehicles, Energy Conversion and Management, 247 (2021), 114676
  12. Ma, Y., et al., A Novel Method for State of Health Estimation of Lithium-Ion Batteries Based on Improved LSTM and Health Indicators Extraction, Energy, 251 (2022), 123973
  13. Nie, J., et al., Identification of Different Colored Plastics by Laser-Induced Breakdown Spectroscopy Combined with Neighborhood Component Analysis `and Support Vector Machine, Polymer Testing, 112 (2022), 107624
  14. Han, X., Dong, J., Applications of Fractional Gradient Descent Method with Adaptive Momentum in BP Neural Networks, Applied Mathematics and Computation, 448 (2023), C, 127994
  15. Chen, J., et al., Improved Gradient Descent Algorithms for Time-Delay Rational State-Space Systems: Intelligent Search Method and Momentum Method, Non-Linear Dynamics, 101 (2020), 1, pp. 361-373

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence