scholarly journals Optimal Line Pressure Control for an Automatic Transmission-Based Parallel Hybrid Electric Vehicle considering Mode Change and Gear Shift

2014 ◽  
Vol 6 ◽  
pp. 216098 ◽  
Author(s):  
Minseok Song ◽  
Joseph Oh ◽  
Seokhwan Choi ◽  
Youngchul Kim ◽  
Hyunsoo Kim

An optimal line pressure control algorithm was proposed for the fuel economy improvement of an AT-based parallel hybrid electric vehicle (HEV). By performing lever analysis at each gear step, the required line pressure was obtained considering the torque ratio of the friction elements. In addition, the required line pressure of the mode clutch was calculated. Based on these results, the optimal line pressure map at each gear step of the EV and HEV modes was presented. Using the line pressure map, an optimal line pressure was performed for the AT input torque and mode. To investigate the proposed line pressure control algorithm, a HEV performance simulator was developed based on the powertrain model of the target HEV, and fuel economy improvement was evaluated. Simulation results showed that as the gear step became higher, the optimal line pressure control could reduce the hydraulic power loss, which gave a 2.2% fuel economy improvement compared to the existing line pressure control for the FTP-72 mode.

Author(s):  
Christian M. Muehlfeld ◽  
Sudhakar M. Pandit

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.


2011 ◽  
Vol 228-229 ◽  
pp. 951-956 ◽  
Author(s):  
Yun Bing Yan ◽  
Fu Wu Yan ◽  
Chang Qing Du

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.


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