Study on the Energy Recovery Ability of Hybrid Tractor Based on Advisor

2015 ◽  
Vol 757 ◽  
pp. 185-190
Author(s):  
Li Hao Yang ◽  
You Jun Wang ◽  
Qiu Juan Lv
Keyword(s):  
Simulation Model ◽  
Working Conditions ◽  
Hybrid System ◽  
Control Strategy ◽  
Energy Recovery ◽  
Adaptive Fuzzy Control ◽  
The Self ◽  
Secondary Development ◽  
Development Technology ◽  
Fuzzy Control Strategy

Energy recovery ability is one of the most important ability of the hybrid system. In this paper, we established a simulation model of a 10T hybrid tractor under researching in advisor by the secondary development technology. And then we carried out the simulation which provides many important curves about the energy recovery ability and some other important abilities under the working conditions of 5 peak cycle using the self-adaptive fuzzy control strategy. The results of the simulation prove that the recovery ability of the hybrid tractor satisfy the design goals well.

A Research on the Fuzzy Control Strategy for Parallel Hybrid Electric Vehicle

2011 ◽  
Vol 121-126 ◽  
pp. 2522-2526
Author(s):  
Ling Cai ◽  
Liang Ge
Keyword(s):  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Secondary Development ◽  
Simulation Results ◽  
Hybrid Electric ◽  
Fuzzy Control Strategy

Several kinds of methods of energy management of hybrid electric vehicle (HEV) are analyzed. Based on the design requirement of a certain type of parallel HEV, the fuzzy control strategy of energy management is proposed. ADVISOR2002 is chosen as the simulation platform for secondary development, and the simulation results of the fuzzy control strategy and electric assist control strategy are compared. The simulation results indicate that the adaptive fuzzy controller can obviously improve the performance of HEV fuel economy and emissions.

Analysis on Composite Action Control Strategy of Separate Meter-In Separate Meter-Out Control System

2014 ◽  
Vol 721 ◽  
pp. 342-348
Author(s):  
Wan Rong Wu ◽  
Jian Chao Yao
Keyword(s):  
Control System ◽  
Simulation Model ◽  
Working Conditions ◽  
Control Strategy ◽  
Hydraulic System ◽  
System Model ◽  
Transmission Model ◽  
Composite Action ◽  
Composite Control ◽  
Actuator System

Based on the shortcomings of traditional multi actuator composite action on its coordination and load adaptability, this paper has put forward a hydraulic system model where separate meter-in separate meter-out controls the multi actuator, according to different action working conditions of actuator, it has provided a composite control strategy based on pressure flow, and through AMEsim and MATLAB, it has established the composite action hydraulic transmission model of double-actuator system and simulation model of control system, and then conducted co-simulation to verify the designed controller’s good coordination and load adaptability to the separate meter-in and separate meter-out control system under different composite action working conditions.

Design and Simulation of Power System for Hybrid Sweeper Truck

2013 ◽  
Vol 389 ◽  
pp. 435-440
Author(s):  
Bing Li Zhang ◽  
Lun Zhen Wang ◽  
Fu Bin Xiao ◽  
Xin Ying Ou
Keyword(s):  
Power System ◽  
Simulation Model ◽  
Fuel Consumption ◽  
Hybrid System ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Simulation Results ◽  
And Control

A hybrid system scheme was designed for the sweeper truck, to solve the problems of high fuel consumption and poor emission performance of traditional sweeper. The control strategy was determined for the hybrid power system. The simulation model of hybrid sweeper truck was built with Matlab/Simulink, and off-line simulation was completed to verify the power system scheme and control strategy, the simulation results indicate that the hybrid sweep truck can realize functions of sweeper and improve the fuel economy.

scholarly journals Research on Establishment of Vehicle Energy Distribution Model and Energy Consumption Optimization Based on Electric Hybrid System

2021 ◽  
Vol 12 (4) ◽  
pp. 213
Author(s):  
Peng Liang ◽  
Huatuo He ◽  
Huafang Cui ◽  
Minglang Zhang
Keyword(s):  
Energy Consumption ◽  
Energy Distribution ◽  
Working Conditions ◽  
Hybrid System ◽  
Control Strategy ◽  
Optimization Method ◽  
Distribution Model ◽  
Average Efficiency ◽  
Energy Consumption Analysis ◽  
Energy Consumption Optimization

In order to improve the adaptability and accuracy of the system average efficiency model in energy consumption analysis of working conditions, this paper presents a vehicle energy distribution model based on the layout and powertrain operation features of the electric hybrid system, and presents a vehicle energy consumption optimization method for control strategy and hardware quality optimization based on the guidance of the energy distribution model.

scholarly journals Energy Control Strategy of Fuel Cell Hybrid Electric Vehicle Based on Working Conditions Identification by Least Square Support Vector Machine

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 426 ◽  
Author(s):  
Yongliang Zheng ◽  
Feng He ◽  
Xinze Shen ◽  
Xuesheng Jiang
Keyword(s):  
Support Vector Machine ◽  
Fuel Cell ◽  
Fuzzy Control ◽  
Working Conditions ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Least Square ◽  
Support Vector ◽  
Fuzzy Control Strategy

Aimed at the limitation of traditional fuzzy control strategy in distributing power and improving the economy of a fuel cell hybrid electric vehicle (FCHEV), an energy management strategy combined with working conditions identification is proposed. Feature parameters extraction and sample divisions were carried out for typical working conditions, and working conditions were identified by the least square support vector machine (LSSVM) optimized by grid search and cross validation (CV). The corresponding fuzzy control strategies were formulated under different typical working conditions, in addition, the fuzzy control strategy was optimized with total equivalent energy consumption as the goal by particle swarm optimization (PSO). The adaptive switching of fuzzy control strategies under different working conditions were realized through the identification of driving conditions. Results showed that the fuzzy control strategy with the function of driving conditions identification had a more efficient power distribution and better economy.

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