THERMAL SCIENCE

International Scientific Journal

Thermal Science - Online First

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Stefan V. Milićević

,

Ivan A. Blagojević

online first only

Managing fuel consumption and emissions for hybrid electric vehicles through optimization of engine operation

ABSTRACT
This paper presents a multi-objective optimization framework for improving internal combustion engine performance in hybrid electric vehicles, specifically targeting the minimization of fuel consumption and emissions (CO, NOx, HC, PM). The proposed method integrates normalized objective functions with weighted factors to develop a unified performance index, facilitating the simultaneous optimization of multiple conflicting objectives. Utilizing the NSGA-II algorithm, a diverse set of Pareto optimal points is generated, each representing different trade-offs between the objectives. The study's results demonstrate significant improvements in engine performance through the application of the unified ICE operation map, showcasing a notable reduction in emissions with only a slight increase in fuel consumption. The methodology was validated via MATLsimulations on two case studies involving parallel and series hybrid electric vehicles, employing a custom synthesized drive cycle for energy management strategy evaluation. The unified map enabled real-time control and efficiency improvements by balancing different emission parameters, thus optimizing ICE operation across various conditions.
KEYWORDS
internal combustion engine, engine optimization, hybrid electric vehicle, multi-objective optimization, Fuel economy, pollutant emission
PAPER SUBMITTED: 2024-11-24
PAPER REVISED: 2024-12-31
PAPER ACCEPTED: 2025-01-06
PUBLISHED ONLINE: 2025-02-16
DOI REFERENCE: https://doi.org/10.2298/TSCI241124025M
REFERENCES
  1. Alshehry, A. S., and Belloumi, M., Study of the environmental Kuznets curve for transport carbon dioxide emissions in Saudi Arabia, Renewable and Sustainable Energy Reviews, 75 (2017), pp. 1339-1347
  2. Blagojević, I., et al. ,The future (and the present) of motor vehicle propulsion systems, Thermal Science 23.Suppl. 5 (2019): 1727-1743
  3. Zahedi, S., et al., Exploring the public's willingness to reduce air pollution and greenhouse gas emissions from private road transport in Catalonia, Science of the Total Environment, 646 (2019), pp. 850-861
  4. Hooftman, N., et al., A review of the European passenger car regulations--Real driving emissions vs local air quality, Renewable and Sustainable Energy Reviews, 86 (2018), pp. 1-21
  5. Huang, Y., et al., Fuel consumption and emissions performance under real driving: Comparison between hybrid and conventional vehicles, Science of the Total Environment, 659 (2019), pp. 275-282
  6. Cao, Yunfei, Ming Yao, and Xiaodong Sun. "An overview of modelling and energy management strategies for hybrid electric vehicles." Applied Sciences 13.10 (2023): 5947
  7. Mohammed, Adem Siraj, et al. "Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles." Energy Reports 9 (2023): 2213-2228
  8. Hannan, M. A., et al., Hybrid electric vehicles and their challenges: A review, Renewable and Sustainable Energy Reviews, 29 (2014), pp. 135-150
  9. Yang, C., et al., Efficient energy management strategy for hybrid electric vehicles/plug-in hybrid electric vehicles: review and recent advances under intelligent transportation system, IET Intelligent Transport Systems, 14 (2020), 7, pp. 702-711
  10. Singh, K. V., et al., Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series--parallel hybrid electric vehicle to improve fuel economy, Electrical Engineering, 102 (2020), pp. 967-987
  11. Panday, A., and Bansal, H. O., A review of optimal energy management strategies for hybrid electric vehicle, International Journal of Vehicular Technology, 2014, pp. 1-19
  12. Liu, T., et al., Reinforcement learning optimized look-ahead energy management of a parallel hybrid electric vehicle, IEEE/ASME Transactions on Mechatronics, 22 (2017), 4, pp. 1497-1507
  13. Milićević, S. V., et al., Advanced rule-based energy management for better fuel economy of hybrid electric tracked vehicle, FME Transactions, 49 (2021), 3, pp. 711-718
  14. Roy, H. K., et al., Real-world investigation of a methodology for powertrain component sizing of hybrid electric vehicles, Proceedings, 2013 World Electric Vehicle Symposium and Exhibition (EVS27), IEEE, Barcelona, Spain, 2013, pp. 1-9
  15. Chung, I., et al., Fuel economy improvement analysis of hybrid electric vehicle, International Journal of Automotive Technology, 20 (2019), pp. 531-537
  16. Zhang, F., et al., Energy management strategies for hybrid electric vehicles: Review, classification, comparison, and outlook, Energies, 13 (2020), 3352
  17. Madanipour, V., et al., Multi-objective component sizing of plug-in hybrid electric vehicle for optimal energy management, Clean Technologies and Environmental Policy, 18 (2016), pp. 1189-1202
  18. Poursamad, A., and Montazeri, M., Design of genetic-fuzzy control strategy for parallel hybrid electric vehicles, Control Engineering Practice, 16 (2008), 7, pp. 861-873
  19. Benaitier, Alexis, et al. "Optimal energy management of hybrid electric vehicles considering pollutant emissions during transient operations." Applied Energy 344 (2023): 121267
  20. Wu, X., et al., Application of particle swarm optimization for component sizes in parallel hybrid electric vehicles, Proceedings, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), IEEE, Hong Kong, China, 2008, pp. 2874-2878
  21. Desai, C., and Williamson, S. S., Particle swarm optimization for efficient selection of hybrid electric vehicle design parameters, Proceedings, 2010 IEEE Energy Conversion Congress and Exposition, IEEE, Atlanta, Ga., USA, 2010, pp. 1623-1628
  22. Malikopoulos, A. A., Impact of component sizing in plug-in hybrid electric vehicles for energy resource and greenhouse emissions reduction, Journal of Energy Resources Technology, 135 (2013), 4, 041201
  23. Piccolo, A., et al., Optimisation of energy flow management in hybrid electric vehicles via genetic algorithms, Proceedings, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. IEEE, Como, Italy, 2001, Vol. 1, pp. 434-439
  24. Ding, N., K. Prasad, and T. T. Lie. "Design of a hybrid energy management system using designed rule‐based control strategy and genetic algorithm for the series‐parallel plug‐in hybrid electric vehicle." International Journal of Energy Research 45.2 (2021): 1627-1644
  25. Katrašnik, T., Hybridization of powertrain and downsizing of IC engine--A way to reduce fuel consumption and pollutant emissions--Part 1, Energy Conversion and Management, 48 (2007), 5, pp. 1411-1423
  26. Milićević, S. V., and Blagojević, I. A., Powertrain Optimization Methodology Based on Scalable Modeling, Proceedings, 2023 31st Telecommunications Forum (TELFOR), IEEE, Belgrade, Serbia, 2023, pp. 1-4
  27. Zhang, B., et al., Quantitative analysis of the energy saving mechanism of a hybrid electric tracked vehicle by an analytical method, Energy Conversion and Management, 237 (2021), 114067
  28. Ahn, K., and Papalambros, P. Y., Engine optimal operation lines for power-split hybrid electric vehicles, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 223 (2009), 9, pp. 1149-1162
  29. Ahn, K., et al., Engine operation for the planetary gear hybrid powertrain, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 220 (2006), 12, pp. 1727-1735
  30. Zhang, B., et al., Adaptive smoothing power following control strategy based on an optimal efficiency map for a hybrid electric tracked vehicle, Energies, 13 (2020), 8, 1893
  31. Wang, H., et al., Dynamic modeling and control strategy optimization for a hybrid electric tracked vehicle, Mathematical Problems in Engineering, 2015
  32. Montazeri-Gh, M., et al., Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles, Journal of the Franklin Institute, 343 (2006), 4-5, pp. 420-435
  33. Delkhosh, M., et al., Optimization of power train and control strategy of hybrid electric vehicles, Scientia Iranica, 22 (2015), 5, pp. 1842-1854
  34. Li, X., and Evangelou, S. A., Torque-leveling threshold-changing rule-based control for parallel hybrid electric vehicles, IEEE Transactions on Vehicular Technology, 68 (2019), 7, pp. 6509-6523
  35. Shabbir, W., and Evangelou, S. A., Real-time control strategy to maximize hybrid electric vehicle powertrain efficiency, Applied Energy, 135 (2014), pp. 512-522
  36. Markel, T., et al., ADVISOR: a systems analysis tool for advanced vehicle modeling, Journal of Power Sources, 110 (2002), 2, pp. 255-266
  37. Kim, I. Y., and De Weck, O. L., Adaptive weighted-sum method for bi-objective optimization: Pareto front generation, Structural and Multidisciplinary Optimization, 29 (2005), pp. 149-158
  38. Shen, G., Design of new clean and efficient combustion mode and thermodynamics research using NSGA-II algorithm, Thermal Science 24.5 Part A (2020): 2699-2706
  39. Milićević, S. V., and Blagojević, I. A., Component sizing and energy management for a series hybrid electric tracked vehicle, Vojnotehnički glasnik/Military Technical Courier, 70 (2022), 4, pp. 877-896
  40. Milićević, S., et al., Numerical Analysis of Optimal Hybridization in Parallel Hybrid Electric Powertrains for Tracked Vehicles, Energies, 17 (2024), 14, 3531
  41. Shen, Yongpeng, et al. "Optimization of fuel consumption and emissions for auxiliary power unit based on multi-objective optimization model." Energies 9.2 (2016): 90
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Managing fuel consumption and emissions for hybrid electric vehicles through optimization of engine operation