Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system

Du, Jiuyu; Zhang, Xiaobin; Wang, Tianze; Song, Ziyou; Yang, Xueqing; Wang, Hewu; Ouyang, Minggao; Wu, Xiaogang

doi:10.1016/j.energy.2018.09.084

Cited by 76 publications

(31 citation statements)

References 19 publications

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“…Another good study from the same research group [28] proposed a soft-run strategy for real-time and multi-objective control algorithm design. Du et al [29] proposed an algorithm based on two-dimensional Pontryagin's minimum principle to distribute power for PHEV with multi-energy storage system, and simulation results showed that the total vehicle operating cost was significantly reduced compared to the PHEV with BESS. DP approach [30,31] has been employed to develop optimal control strategy for the HESS in a PHEV.…”

Section: B Energy Management Strategymentioning

confidence: 99%

Optimal Design of a Hybrid Energy Storage System in a Plug-In Hybrid Electric Vehicle for Battery Lifetime Improvement

Bai

et al. 2020

IEEE Access

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Section: B Energy Management Strategymentioning

confidence: 99%

Optimal Design of a Hybrid Energy Storage System in a Plug-In Hybrid Electric Vehicle for Battery Lifetime Improvement

Bai

et al. 2020

IEEE Access

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“…The minimum principle can be expressed as: the optimal trajectory determined by the optimal control law must be the minimum value within the whole control domain when the control variables are limited to a certain range, which can be applied in the energy management for HEVs. The PMP [72,73] method solves the optimal energy management by finding the instantaneous minimum value of Hamiltonian function at each moment, which is generally defined as the derivative of the stage cost function versus time represented by the adjustable variable as independent variable. The optimal control variables U will be obtained when the derivative of Hamiltonian function H versus control variables equals to 0, that is, ∂H/∂U = 0.…”

Section: Pontryagin's Minimum Principle (Pmp)mentioning

confidence: 99%

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Kong

Liang

et al. 2019

Applied Sciences

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This paper presents a comprehensive review of energy management control strategies utilized in hybrid electric vehicles (HEVs). These can be categorized as rule-based strategies and optimization-based strategies. Rule-based strategies, as the most basic strategy, are widely used due to their simplicity and practical application. The focus of rule-based strategies is to determine and optimize the optimal threshold for mode switching; however, they fall into a local optimal solutions. To have better performance in energy management, optimization-based strategies were developed. The categories of the existing optimization-based strategies are identified from the latest literature, and a brief study of each strategy is discussed, which consists of the main research ideas, the research focus, advantages, disadvantages and improvements to ameliorate optimality and real-time performance. Deterministic dynamic programming strategy is regarded as a benchmark. Based on neural network and the large data processing technology, data-driven strategies are put forward due to their approximate optimality and high computational efficiency. Finally, the comprehensive performance of each control strategy is analyzed with respect to five aspects. This paper not only provides a comprehensive analysis of energy management control strategies for HEVs, but also presents the emphasis in the future.

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“…Adding the fact that BTs have a shorter lifetime than power electronic systems, the BT system is identified as a bottleneck in the lifetime of the bus. Moreover, that BT pack replacements are required, this affects significantly to the operation costs during the vehicle lifetime [3], [4], increasing the total cost of ownership (TCO). Therefore, it can be said that the BT lifetime is closely related to vehicle operation.…”

Section: Introductionmentioning

confidence: 99%

“…The SOH enables to act to manage the BT lifetime in a long term scope. In [4], Du J. et. al propose an EMS for an hybrid electric bus (HEB) with a hybrid energy storage system (HESS), to minimize the BT degradation and total costs.…”

Section: Introductionmentioning

confidence: 99%

Li-ion Battery Aging Conscious Intelligent Energy Management Strategy for Hybrid Electric Buses

Ibarra¹,

Lucu²,

Goitia-Zabaleta³

et al. 2019

Perspectivas

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The aim of this paper is to propose a battery aging conscious energy management strategy. The initial design of an energy management strategy is a significant point, in order to fulfill the efficiency goals in a short term. However, with the aging, the initial conditions vary. The new trend of digitalization allows to monitor the operation, having the possibility to improve the performance of the initial proposed strategy in a long term. Therefore, a methodology for updating the energy management strategy along the bus lifetime is proposed, in order to improve the operation costs and extend the battery lifetime. This methodology is based on a dynamic programming optimization, tuning the membership functions in a fuzzy logic control. The simulation results show a reduction of the operation costs up to 47% together with a BT lifetime extension of around 2.94%.

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Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system

Cited by 76 publications

References 19 publications

Optimal Design of a Hybrid Energy Storage System in a Plug-In Hybrid Electric Vehicle for Battery Lifetime Improvement

Optimal Design of a Hybrid Energy Storage System in a Plug-In Hybrid Electric Vehicle for Battery Lifetime Improvement

Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

Li-ion Battery Aging Conscious Intelligent Energy Management Strategy for Hybrid Electric Buses

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