REAL-TIME SIMULATION AND RESEARCH ON CONTROL ALGORITHM OF PARALLEL HYBRID ELECTRIC VEHICLE

2003 ◽  
Vol 39 (10) ◽  
pp. 156 ◽  
Author(s):  
Yi Tong
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Control Algorithm ◽  
Real Time Simulation ◽  
Parallel Hybrid Electric Vehicle ◽  
Time Simulation ◽  
Parallel Hybrid ◽  
Hybrid Electric

D2P Real-Time Simulation of Energy Management Strategy for Parallel Hybrid Electric Vehicle

2013 ◽  
Vol 278-280 ◽  
pp. 1704-1707
Author(s):  
Ze Yu Chen ◽  
Guang Yao Zhao
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Power Sources ◽  
Real Time Simulation ◽  
Parallel Hybrid Electric Vehicle ◽  
Time Simulation ◽  
Parallel Hybrid ◽  
Hybrid Electric

For investigating the feasibility of control strategy used in parallel hybrid electric vehicle, a D2P real-time simulation is introduced. A new multi-mode rule-based control strategy is proposed. The strategy is based on splitting the torque from the motor and engine so that these power sources can be operated at high efficiency. A real-time simulation platform is built based on D2P system. Real driver inputs and controller are applied while controlled objects are simulated using the model of parallel hybrid electric system computed in D2P module. Strategy is validated by D2P real-time simulation, which results show that the presented strategy is feasible and effective.

Research on Dynamic Torque Control Strategy for Parallel Hybrid Electric Vehicle

2011 ◽  
Vol 228-229 ◽  
pp. 951-956 ◽  
Author(s):  
Yun Bing Yan ◽  
Fu Wu Yan ◽  
Chang Qing Du
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Control Algorithm ◽  
Dynamic Control ◽  
Torque Control ◽  
Engine Torque ◽  
Parallel Hybrid Electric Vehicle ◽  
Torque Control Strategy ◽  
Parallel Hybrid ◽  
Hybrid Electric

It is necessary for Parallel Hybrid Electric Vehicle (PHEV) to distribute energy between engine and motor and to control state-switch during work. Aimed at keeping the total torque unchanging under state-switch, the dynamic torque control algorithm is put forward, which can be expressed as motor torque compensation for engine after torque pre-distribution, engine speed regulation and dynamic engine torque estimation. Taking Matlab as the platform, the vehicle control simulation model is built, based on which the fundamental control algorithm is verified by simulation testing. The results demonstrate that the dynamic control algorithm can effectively dampen torque fluctuations and ensures power transfer smoothly under various state-switches.

Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle

2011 ◽  
Vol 226 (2) ◽  
pp. 188-203 ◽  
Author(s):  
V T Minh ◽  
F B Mohd Hashim ◽  
M Awang
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Parallel Hybrid Electric Vehicle ◽  
Transition Strategy ◽  
Output Constraints ◽  
Parallel Hybrid ◽  
Driving Model ◽  
Time Optimal ◽  
Hybrid Electric

The present paper develops a real-time clutch transition strategy for a parallel hybrid electric vehicle (HEV) in order to achieve quick and smooth clutch transition engagements between pure electrical driving and hybrid driving. Model predictive control (MPC) has been used for this model and tested with different control horizons and weighting factors to verify the ability of MPC to control the vehicle speeds for the clutch engagement. Some modified MPC algorithms with softened constraints and with output regions have been also studied to improve the robustness and the ability of this controller. Comprehensive simulations for the HEV have been conducted in MATLAB and Simulink. Results show that the system can provide real-time optimal control actions subject to input and output constraints for real-time clutch transition engagement with high driving comfort. The system can be implemented in electronic control units and applied for real HEVs.

Speed and Throttle Position Forecasting on a Parallel Hybrid Electric Vehicle

2003 ◽  
Author(s):  
Christian M. Muehlfeld ◽  
Sudhakar M. Pandit
Keyword(s):  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Control Algorithm ◽  
Feedforward Control ◽  
Vehicle Simulation ◽  
The Road ◽  
Parallel Hybrid Electric Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric

Included in this paper is the forecasting of the speed and throttle position on a thru-the-road parallel hybrid electric vehicle (HEV). This thru-the-road parallel hybrid design is implemented in a 2002 model year Ford Explorer XLT, which is also the Michigan Tech Future Truck. Data Dependent Systems (DDS) forecasting is used in a feedforward control algorithm to improve the fuel economy and to improve the drivability. It provides a one step ahead forecast, thereby allowing the control algorithm to always be a step ahead, utilizing the engine and electric motor in their most efficient ranges. This control algorithm is simulated in PSAT, a hybrid vehicle simulation package, which can estimate the fuel economy and certain performance characteristics of the vehicle. In this paper a fuel economy savings of 2.2% is shown through simulation. Charge sustainability was achieved along with drivability being improved as indicated by the reduction in number of deviations from the speed profile in the driving cycle.

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