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Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation

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  • Jiajun Liu

    (School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
    Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W2Y2, Canada)

  • Huachao Dong

    (Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W2Y2, Canada)

  • Tianxu Jin

    (School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Li Liu

    (School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Babak Manouchehrinia

    (Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W2Y2, Canada)

  • Zuomin Dong

    (Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W2Y2, Canada)

Abstract

In this paper, identification of an appropriate hybrid energy storage system (HESS) architecture, introduction of a comprehensive and accurate HESS model, as well as HESS design optimization using a nested, dual-level optimization formulation and suitable optimization algorithms for both levels of searches have been presented. At the bottom level, design optimization focuses on the minimization of power loss in batteries, converter, and ultracapacitors (UCs), as well as the impact of battery depth of discharge (DOD) to its operation life, using a dynamic programming (DP)-based optimal energy management strategy (EMS). At the top level, HESS optimization of component size and battery DOD is carried out to achieve the minimum life-cycle cost (LCC) of the HESS for given power profiles and performance requirements as an outer loop. The complex and challenging optimization problem is solved using an advanced Multi-Start Space Reduction (MSSR) search method developed for computation-intensive, black-box global optimization problems. An example of load-haul-dump (LHD) vehicles is employed to verify the proposed HESS design optimization method and MSSR leads to superior optimization results and dramatically reduces computation time. This research forms the foundation for the design optimization of HESS, hybridization of vehicles with dynamic on-off power loads, and applications of the advanced global optimization method.

Suggested Citation

  • Jiajun Liu & Huachao Dong & Tianxu Jin & Li Liu & Babak Manouchehrinia & Zuomin Dong, 2018. "Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation," Energies, MDPI, vol. 11(10), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2699-:d:174710
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    References listed on IDEAS

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