Abstract
This paper addresses optimization for hybrid electric vehicle (HEV) by using a single agent method to optimize the power losses and fuel consumption under a specific driving cycle base on Safe Experimentation Dynamics (SED) method. For optimization process, four gain are added in four main parts of the HEV system. Those main parts are engine, motor, generator and battery. These four gain are controlled the output for each components to give the minimum power losses. The design method is applied to free model of HEV by using Simulink/MATLAB software while M-File/MATLAB is used to apply the Safe Experimentation Dynamics (SED) method. The result from design method achieved minimum reduction of power losses and fuel consumption compared to original system. Thus, the comparison of the simulation results shown that the algorithm approach provides better performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmad, M.A., Azuma, S.I., Baba, I., Sugie, T.: Switching controller design for hybrid electric vehicles. SICE J. 7(5), 273–282 (2014)
Wang, Q., Frank, A.A.: Plug-in HEV with CVT: configuration, control, and its concurrent multi-objective optimization by evolutionary algorithm. Int. J. Automot. Technol. 15(1), 103–115 (2014)
Abdul Shukor, N.S., Ahmad, M.A., Zaidi, M., Tumari, M.: Data-driven PID tuning based on safe experimentation dynamics for control of liquid slosh. In: 8th IEEE Control and System Graduate Research Colloquium (ICSGRC 2017), Shah Alam, Malaysia, 4–5 August 2017, pp. 1–5 (2017)
Panday, A., Bansal, H.O.: A review of optimal energy management strategies for hybrid electric vehicle. Int. J. Veh. Technol. 2014, 1–19 (2014)
Prokhorov, D.: Toyota Prius HEV neurocontrol. In: Proceedings of International Joint Conference on Neural Networks (2007)
Ahmad, M.A., Baba, I., Azuma, S.I., Sugie, T.: Model free tuning of variable state of charge target of hybrid electric vehicles. The International Federation of Automatic Control (2013)
Spall, J.C.: An overview of simultaneous perturbation method for efficient optimization. John Hopkins APL Tech. Digest 19(4), 482–492 (1998)
Acknowledgement
This research study is supported by Ministry of Higher Education Malaysia (MoHE) and Universiti Malaysia Pahang under Fundamental Research Grant Scheme FRGS/1/2017/TK04/UMP/03/1 or RDU 170129.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
bin Mohd Rashid, M.I., Daniyal, H., Ahmad, M.A. (2019). Energy Management Strategy (EMS) for Hybrid Electric Vehicles Based on Safe Experimentation Dynamics (SED). In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11656. Springer, Cham. https://doi.org/10.1007/978-3-030-26354-6_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-26354-6_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-26353-9
Online ISBN: 978-3-030-26354-6
eBook Packages: Computer ScienceComputer Science (R0)