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Random Search in Energy Management Strategy (EMS) for Hybrid Electric Vehicles

  • Muhammad Syahmi GhazaliEmail author
  • Muhammad Ikram Mohd Rashid
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 538)

Abstract

The aim of this project is to optimize the total energy used (summation fuel and electricity) from vehicle utilization with the initial result in hybrid electric car (HEV) by using an optimization called Random Search Optimization. Nowadays, the developments of hybrid electric cars are not something new. There are a lot of research are being done on how to increase the effectiveness of hybrid electric cars. One of the main aspects that are being aim is to reduce the electricity consumption while increasing the HEV performance. This is for maintain or increase the HEV performance which is increase the efficiency. Thus, Random Search Optimization was applied to optimize the HEV source output which is from electricity system. This method also had already been applied to solve several other problems. But for HEV optimization more research is needed so that it can be applied for real HEV development in industry not for simulation purpose only.

Keywords

HEV Random search Optimization 

References

  1. 1.
    Geller, B.M.: Increased understanding of hybrid vehicle design through modeling, simulation, and optimization. Colorado State University, Colorado (2010)Google Scholar
  2. 2.
    Yongqin, Z.J.: Power Battery Charging State-of-Charge Prediction Based on Genetic Neural Network (2010)Google Scholar
  3. 3.
    Park, J., Park, J.H.: Development of equivalent fuel consumption minimization strategy for hybrid electric vehicles. Int. J. Autom. Technol. 13(5), 835–843 (2002)CrossRefGoogle Scholar
  4. 4.
    Ahmad, M.A.: Model Free Tuning of Variable State of Charge Target of Hybrid Electric Vehicles (2013)CrossRefGoogle Scholar
  5. 5.
    Spall, J.C.: Introduction To Stochastic Search And Optimization: Estimation, Simulation, and Control. Wiley Interscience (2003)Google Scholar
  6. 6.
    Sankar, P., Kruthiventi, K.K.P.: A New Random Search Algorithm: Multiple Solution Vector Approach (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Muhammad Syahmi Ghazali
    • 1
    Email author
  • Muhammad Ikram Mohd Rashid
    • 1
  1. 1.Faculty of Electrical and Electronic EngineeringUniversity Malaysia PahangPekanMalaysia

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