Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

Real-Time Simulation Study for a Series Hybrid Electric Vehicle

2011 ◽  
Vol 128-129 ◽  
pp. 965-969
Author(s):  
Xu Dong Liu ◽  
Qing Wu Fan ◽  
Bang Gui Zheng ◽  
Jian Min Duan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Real Time Simulation ◽  
Logic Control ◽  
Time Simulation ◽  
Series Hybrid Electric Vehicle

To shorten design period and reduce development costs, computer modeling & simulation is important for HEV design and development. In this paper, real-time simulation for a Series Hybrid Electric Vehicle (SHEV) is made to test its fuzzy logic control strategy based on dSPACE-DS1103 development kits. The whole real-time simulation schematic is designed and the vehicle forward-facing simulation model is set up. Driver behavior is simulated by two potentiometers and introduced into the system to realize close-loop control. A real-time monitoring interface is also developed to observe the experiment results. Experiment results show that the real-time simulation platform works well and the SHEV fuzzy logic control strategy is effective.

Fuzzy logic control for a hydraulic hybrid excavator based on torque prediction and genetic algorithm optimization

2017 ◽  
Vol 232 (8) ◽  
pp. 983-994 ◽  
Author(s):  
Hua Zhou ◽  
Peng-Yu Zhao ◽  
Ying-Long Chen
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Membership Functions ◽  
Real Time Control ◽  
Hydraulic Hybrid ◽  
Time Control ◽  
Logic Control ◽  
Hybrid Excavator

Optimization of the control strategy, whose primary mission is to solve the problem associated with energy management, is an effective way to minimize the fuel consumption of the hydraulic hybrid excavator. As a widely used control strategy, fuzzy logic control can be adopted to realize suboptimal power split with robustness and adaptation, which is one of the most logical approaches for multidomain, nonlinear and time-varying plant. However, the membership functions are difficult to determine according to manual experiences; meanwhile, the optimization-based membership functions are difficult to utilize in real time control. This paper aims to improve the fuel consumption of a hydraulic hybrid excavator by proposing a fuzzy control strategy whose membership functions are optimized by the genetic algorithm, which considers predicted torque of the internal combustion engine (ICE) as a known quantity to realize real time control. The needed torque of the ICE is predicted by superposition of the previous torque. A fuzzy logic control strategy is then designed with membership functions optimized by the genetic algorithm according to the predicted needed torque to achieve better performance. Finally, a numerical experiment is carried out to verify the proposed control strategy.

Fuzzy Logic Control Strategy for an Extended-Range Electric Vehicle

2012 ◽  
Vol 220-223 ◽  
pp. 968-972 ◽  
Author(s):  
Ji Gao Niu ◽  
Su Zhou
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
High Efficiency ◽  
Control Strategies ◽  
Vehicle Performance ◽  
Logic Control ◽  
Extended Range ◽  
Avl Cruise

This paper presents a Fuzzy Logic Control Strategy (FLCS) for an Extended-range Electric Vehicle (E-REV) with series structure. The control strategy design objective of the E-REV is fuel economy. Based on the State of Charge (SOC) of the battery and the desired power for driving, the power required by the vehicle is split between the engine/generator set and the battery by the FLCS. The engine can be operated consistently in a very high efficiency area and the SOC of the battery can be maintained at a reasonable level. Some standard driving cycles and two control strategies of Power Follower Control Strategy (PFCS) and FLCS were simulated with AVL-Cruise and Matlab/Simulink to analyze the vehicle performance. Some simulation results are compared and discussed: the FLCS indicates better performance in terms of fuel consumption.

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