Concurrent Optimization for Parameters of Powertrain and Control System of Hybrid Electric Vehicle Based on Multi-Objective Genetic Algorithms

2006 ◽  
Author(s):  
Li-cun Fang ◽  
Shi-yin Qin
Keyword(s):  
Genetic Algorithms ◽  
Control System ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Multi Objective ◽  
Concurrent Optimization ◽  
Hybrid Electric ◽  
And Control

scholarly journals Simultaneous Optimization for Hybrid Electric Vehicle Parameters Based on Multi-Objective Genetic Algorithms

Energies ◽  
2011 ◽  
Vol 4 (3) ◽  
pp. 532-544 ◽  
Author(s):  
Lincun Fang ◽  
Shiyin Qin ◽  
Gang Xu ◽  
Tianli Li ◽  
Kemin Zhu
Keyword(s):  
Genetic Algorithms ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Simultaneous Optimization ◽  
Multi Objective ◽  
Hybrid Electric

Real-Time Modeling, Simulation, and Control System Design of a Dual Hybrid Electric Vehicle

1999 ◽  
Author(s):  
Veronika Gospodareva ◽  
William Hamel ◽  
Claudell Hatmaker ◽  
Jeffrey Hodgson ◽  
Stephen Jesse ◽  
...  
Keyword(s):  
Control System ◽  
System Design ◽  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Control System Design ◽  
Modeling And Control ◽  
Hybrid Electric ◽  
And Control

Abstract The Graduate Automotive Technology Education (GATE) Center at the University of Tennessee, Knoxville (UTK) offers courses addressing the simulation, modeling, and control system design of hybrid electric vehicles (HEV). In the Spring of 1999 such a course was conducted to support the UTK FutureCar Challenge entry for 1999. The vehicle modeled is a Dual-configuration Hybrid Electric Vehicle (DHEV) which uses a planetary power-split device similar to the Toyota Hybrid System used in the Toyota “Prius”. The goals of the course included the development of a real-time simulator that could incorporate actual vehicle control hardware in the simulator loop. This “control-hardware-in-the-loop” (CHIL) configuration was used for simulation, control system design, and troubleshooting. This approach allows the simulation of normal vehicle operating conditions as well as emergency fault handling situations in which it may not be desirable to subject the actual prototype vehicle to a given test condition. Additionally, it is possible to do a great deal of control system testing and development without an operating vehicle.

Modeling and Simulation of a Multiple-Regime Plug-In Hybrid Electric Vehicle

2013 ◽  
Author(s):  
Rui Cheng ◽  
Jian Dong ◽  
Zuomin Dong
Keyword(s):  
Control System ◽  
Modeling And Simulation ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Hybrid Vehicles ◽  
Rule Based ◽  
Hybrid Electric ◽  
Load Leveling ◽  
And Control

In recent years, the automotive industry has devoted considerable resources to the research and development of hybrid vehicles. Plug-in hybrid electric vehicles (PHEV) present to be the next generation hybrid vehicles that offer the advantages in reducing fossil fuel consumption and lowering emissions without sacrifice vehicle performance, and the ability to utilize renewable energy through charge from the electric grid. In this work, the powertrain model of a series-parallel, multiple-regime plug-in hybrid electric vehicle (SPMR-PHEV) was introduced. As one of the several parallel powertrain modeling, simulation and control system design approaches at University of Victoria, the presented SPMR-PHEV model was developed using rule-based load-leveling energy management strategy (EMS) under the MATLAB/Simulink and SimDriveline environment. In order to validate the model and evaluate the fuel consumption and performance of SPMR-PHEV, a Simulink based Prius model and two different PHEV powertrain models have also been built using Autonomie — a vehicle simulation tool developed by DOE’s Argonne National Laboratory, using the default control logics. Fuel consumption from the three different models were compared using a test drive case consisting of eight times of the US06-City drive cycle. Under the static modeling and simulation method and different control strategies, the SPMR-PHEV model in Simulink/SimDriveline and rule-based load-leveling EMS showed 12.02% fuel economy and powertrain efficiency improvements over the Autonomie model. The new powertrain system model developed using Simulink and SimDrivline could also be used as a generic, modular and flexible vehicle modeling platform to support the integration of powertrain design and control system optimization.

Design and Implementation of Hybrid Electric Vehicle Control System CAN Communication

2011 ◽  
Vol 179-180 ◽  
pp. 359-364
Author(s):  
Jing Lian ◽  
Ya Fu Zhou ◽  
Xin Han Sun ◽  
Bao Yu Tian ◽  
Chang Jia Lin
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Can Bus ◽  
Experimental Result ◽  
Control Network ◽  
Application Layer ◽  
Hybrid Electric ◽  
And Control ◽  
Stable Signal

Based on the vehicle CAN bus technology, with features of Hybrid Electric Vehicle (HEV) control network be concerned, CAN bus protocols of application layer suitable for HEV are developed in the paper. And control network is built based on multi-master CAN distributed control technology. Through CAN controller programming of DSP, supported by the corresponding external drive circuit, the motor controller nodes is connected with the vehicle CAN network. Finally the CAN Bus communication of HEV energy assembly control system is designed and realized. Experimental result indicates that the system works well with stable signal and strong anti-jamming ability, and the communication with HEV CAN bus is realized successfully.

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