A Rule Based Energy Management System of Experimental Battery/Supercapacitor Hybrid Energy Storage System for Electric Vehicles

Zhang, Qiao; Deng, Weiwen; Zhang, Sumin; Wu, Jian

doi:10.1155/2016/6828269

Cited by 36 publications

(12 citation statements)

References 31 publications

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“…A rule-based EMS is proposed in [49] that is a semi-active hybrid topology. It exhibits the attributes of the UC and prolongs the battery lifetime.…”

Section: ) Rule-based Energy Management Strategy (Ems)mentioning

confidence: 99%

Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications

et al. 2021

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Choice of hybrid electric vehicles (HEVs) in transportation systems is becoming more prominent for optimized energy consumption. HEVs are attaining tremendous appreciation due to their ecofriendly performance and assistance in smart grid notion. The variation of energy storage systems in HEV (such as batteries, supercapacitors or ultracapacitors, fuel cells, and so on) with numerous control strategies create variation in HEV types. Therefore, choosing an appropriate control strategy for HEV applications becomes complicated. This paper reflects a comprehensive review of the imperative information of energy storage systems related to HEVs and procurable optimization topologies based on various control strategies and vehicle technologies. The research work classifies different control strategies considering four configurations: fuel cell-battery, battery-ultracapacitor, fuel cell-ultracapacitor, and battery-fuel cellultracapacitor. Relative analysis among different control techniques is carried out based on the control aspects and operating conditions to illustrate these techniques' pros and cons. A parametric comparison and a crosscomparison are provided for different hybrid configurations to present a comparative study based on dynamic performance, battery lifetime, energy efficiency, fuel consumption, emission, robustness, and so on. The study also analyzes the experimental platform, the amelioration of driving cycles, mathematical models of each control technique to demonstrate the reliability in practical applications. The presented recapitulation is believed to be a reliable base for the researchers, policymakers, and influencers who continuously develop HEVs with energy-efficient control strategies.

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“…A rule-based EMS is proposed in [49] that is a semi-active hybrid topology. It exhibits the attributes of the UC and prolongs the battery lifetime.…”

Section: ) Rule-based Energy Management Strategy (Ems)mentioning

confidence: 99%

Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications

et al. 2021

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“…The supercapacitor is a high power density with a high number of charging/discharging cycles. Thus, the combination of battery and supercapacitor can provide a complementary advantage to meet the load demand [16].…”

Section: Hps Topology Structure and Modelingmentioning

confidence: 99%

Optimal Adaptive Gain LQR-based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System

Ferahtia¹,

Djerioui²,

Mesbahi³

et al. 2021

Preprint

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This paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery-supercapacitor hybrid power system. The hybrid power system consists of a Lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC-DC converter model is derived utilizing the first-principles method and compute the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power ele-ments’ life expectancies and supplies the power system with the required power

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“…It is possible to divide EMS methods used in the battery/UC powered EVs as the rule‐based and optimization‐based methods . The rule‐based methods, deterministic and the fuzzy rule‐based methods, are easy for applications, and have tolerances to errors. In the deterministic rule‐based EMS, some scenarios are predetermined for the specific driving profiles.…”

Section: Introductionmentioning

confidence: 99%

Jaya algorithm‐based energy management system for battery‐ and ultracapacitor‐powered ultralight electric vehicle

Demircali

Köroğlu

2020

Int J Energy Res

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Summary To improve the driving performance of the electric vehicles, batteries or ultracapacitors (UCs) are frequently preferred in the energizing systems. In hybrid structures with multiple supply sources, an energy management system (EMS) is needed to improve the system efficiency, and to provide the optimum power sharing between a battery and a UC. The purpose of this study is to investigate the effectiveness of the Jaya optimization method for the urban use of the EMS of an ultralight electric vehicle powered by battery/UC. The performance of the proposed method is compared with dynamic programming (DP) that is one of the global optimization methods and particle swarm optimization (PSO) that is one of the other heuristic methods for real‐time applications. The simulation results show that Jaya‐EMS approached 3.1% to the DP, which yields the optimum result with respect to the total energy loss. In addition, the proposed method yields a loss of less than 1.9% from the PSO‐EMS. If all the above situations are considered, the proposed EMS method has less lossy alternative solution for the real‐time applications.

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A Rule Based Energy Management System of Experimental Battery/Supercapacitor Hybrid Energy Storage System for Electric Vehicles

Cited by 36 publications

References 31 publications

Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications

Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications

Optimal Adaptive Gain LQR-based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System

Jaya algorithm‐based energy management system for battery‐ and ultracapacitor‐powered ultralight electric vehicle

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