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Title: Advanced charging strategies for Lithium-ion batteries in electric vehicles
Author: Liu, Kailong
ISNI:       0000 0004 7224 6835
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2018
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This thesis is focused on the development of advanced charging strategies for Li-ion batteries in electric vehicles. A literature survey about battery charging terminology, infrastructure, objective, and termination condition is presented firstly, followed by the introduction of some traditional but popular charging approaches and their improvement measures. Then some intelligent technologies including battery coupled thermoelectric model, heuristic algorithms such as teaching-learning-based optimization (TLBO) and multi-objective biogeography-based optimization (M-BBO), and generalized predictive control (GPC) are described. These literature surveys and intelligent technologies form the basis to conduct novel battery charging strategies. Then in order to derive an optimal CCCV charging profile, a specific triple-objective function is proposed, where TLBO is used to optimize this triple-objective function. From a higher level perspective, in order to analyse the relation between conflicting charging objectives, a model-based strategy to optimize charging profiles and also balance charging speed, energy conversion and temperature variation is proposed. The corresponding Pareto fronts are obtained by using M-BBO approaches. In addition to the optimization of conflicting objectives by searching the suitable charging profiles, an attempt is made to apply the constrained GPC to maintain the battery internal temperature within a desirable level while achieving fast charging. Simulation results confirm the effectiveness of these proposed charging strategies. All the proposed battery charging strategies in this thesis can be easily extended to other battery types. The results presented in this thesis are not only novel in the methodology development, but also significant in practical applications to manipulate the charge current for battery thermal management, guarantee charging efficiency and prolong battery service lifetime.
Supervisor: Li, Kang ; Douglas, Roy Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available