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

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dc.contributor.authorLiu, Jiajun
dc.contributor.authorDong, Huachao
dc.contributor.authorJin, Tianxu
dc.contributor.authorLiu, Li
dc.contributor.authorManouchehrinia, Babak
dc.contributor.authorDong, Zuomin
dc.date.accessioned2019-09-20T22:44:15Z
dc.date.available2019-09-20T22:44:15Z
dc.date.copyright2018en_US
dc.date.issued2018
dc.description.abstractIn 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.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipSupports from the China Scholarship Council (Grant No. 201706460072), National Natural Science Foundation of China (Grant No. 51805436), Transport Canada, and Seaspan are gratefully acknowledged.en_US
dc.identifier.citationLiu, J., Dong, H., Jin, T., Liu, L., Manouchehrinia, B. & Dong, Z. (2018). Optimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulation. Energies, 11(10), 2699. https://doi.org/10.3390/en11102699en_US
dc.identifier.urihttp://dx.doi.org/10.3390/en11102699
dc.identifier.urihttp://hdl.handle.net/1828/11173
dc.language.isoenen_US
dc.publisherEnergiesen_US
dc.subjectnested optimization
dc.subjecthybrid energy storage system
dc.subjectsurrogate-based optimization method
dc.subjectelectrified vehicles
dc.subject.departmentDepartment of Mechanical Engineering
dc.titleOptimization of Hybrid Energy Storage Systems for Vehicles with Dynamic On-Off Power Loads Using a Nested Formulationen_US
dc.typeArticleen_US

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