Fuzzy Control Based Study on Energy Management System of Electric Vehicle with Dual-Energy Storage System

2014 ◽  
Vol 898 ◽  
pp. 896-899
Author(s):  
Zhi Yu Huang ◽  
Xiao Hua Pu
Keyword(s):  
Energy Storage ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Control Strategy ◽  
Storage System ◽  
Energy Storage System ◽  
Dual Energy ◽  
Energy Management System ◽  
Fuzzy Control Strategy

Regarding to the electric vehicle (EV) with dual-energy storage system (DESS) composed of batteries and ultra-capacitors, study on the structure and drive modes of DESS, after a detailed analysis of energy storage system based on power, resistance and constraints in driving, establish a mathematical model of energy management system of EV with DESS, and an energy management based on the fuzzy control strategy is designed. Finally, a simulation of EV with DESS by using ADVISOR simulation platform is studied, whose results show that the EV with DESS based on fuzzy control strategy can be more effective in distributing power between energy storage systems, and the dynamic performance as well as economic efficiency are also improved

The Simulation Study of Pure Electric Vehicle with Dual-Energy Storage System Based on Matlab/Simulink

2013 ◽  
Vol 437 ◽  
pp. 213-216
Author(s):  
Shuang Du ◽  
Chun Cheng Zuo
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Storage System ◽  
Simulation Models ◽  
Energy Storage System ◽  
Dual Energy ◽  
Matlab Simulink ◽  
Fuzzy Control Strategy ◽  
Ultra Capacitor

Through matlab/simulink, the simulation models of Pure Electric Vehicle (PEV) with Dual-Energy Storage System (DESS) composed of batteries and ultra-capacitor are established. The paper designs the fuzzy control strategy for DESS and puts PEV with DESS and PEV with Single-Energy Storage System (SESS) state of capacity (SOC) of batteries comparison. Also it analyses advantages and prospects of development for PEV with DESS.

scholarly journals Optimization of Hybrid Energy Storage System Control Strategy for Pure Electric Vehicle Based on Typical Driving Cycle

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Kanglong Ye ◽  
Peiqing Li ◽  
Hao Li
Keyword(s):  
Energy Consumption ◽  
Energy Storage ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Storage System ◽  
Energy Storage System ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System ◽  
Fuzzy Control Strategy

Taking a hybrid energy storage system (HESS) composed of a battery and an ultracapacitor as the study object, this paper studies the energy management strategy (EMS) and optimization method of the hybrid energy storage system in the energy management and control strategy of a pure electric vehicle (EV) for typical driving cycles. The structure and component model of the HESS are constructed. According to the fuzzy control strategy, aimed at the roughness of the membership function in EMS, optimization strategies based on a genetic algorithm (GA) and particle swarm optimization (PSO) are proposed; these use energy consumption as their optimal objective function. Based on the improved EV model, the fuzzy control strategy is studied in MATLAB/Advisor, and two control strategies are obtained. Compared with the simulation results based on three driving cycles, urban dynamometer driving schedule (UDDS), new European driving cycle (NEDC), and ChinaCity, the optimum control strategy were obtained. The theoretical minimum energy consumption of HESS was reached by dynamic programming (DP) algorithm in the same simulation environment. The research shows that, compared with the PSO, the output current peak and current fluctuation of the battery optimized by the GA are lower and more stable, and the total energy consumption is reduced by 3–9% in various simulation case studies. Compared with the theoretical minimum value, the deviation of energy consumption simulated by GA-Fuzzy Control is 0.6%.

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

scholarly journals Multi-Objective Fuzzy Logic-Based Energy Management System for Microgrids with Battery and Hydrogen Energy Storage System

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1074 ◽  
Author(s):  
Francisco José Vivas ◽  
Francisca Segura ◽  
José Manuel Andújar ◽  
Adriana Palacio ◽  
Jaime Luis Saenz ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Hydrogen Energy ◽  
Economic Point ◽  
Load Demand

This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.

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