Title :
A coordinated braking torque control scheme for hybrid duty trucks with gear shifting
Author :
Chaoqing Wang ; Tielong Shen ; Haibo Ji ; Hikiri, Kunihiko
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
In this paper, a coordinated braking control scheme is presented for hybrid duty trucks. A key problem to improve the efficiency of regenerative braking without loss of comfortability is the coordinated operation between the regenerative braking and the mechanical braking torque generated by the electrical motor and the air-over-hydraulic brake, respectively. Furthermore the gear shifting operation depending on the structure of powertrain is one more important fact that makes this problem difficult. To perform the coordinated control, a high gain observer is proposed in this paper to estimate the total braking torque acting on the wheel which only requires the wheel speed measurement. Then, based on the estimated torque and the driver´s braking torque demand, a coordinated braking control scheme is constructed with three parts: braking torque distribution, feedforward compensation with the air-over-hydraulic brake, and feedback compensation with electrical motor. Analysis of convergence of the closed loop system is provided and finally, simulation results are demonstrated which was conducted on a physically scaled hybrid duty truck.
Keywords :
closed loop systems; compensation; electric motors; feedforward; gears; hybrid electric vehicles; hydraulic systems; observers; power transmission (mechanical); regenerative braking; torque control; velocity measurement; wheels; air-over-hydraulic brake; braking torque distribution; closed loop system; coordinated braking torque control scheme; coordinated operation; electrical motor; feedback compensation; feedforward compensation; gear shifting operation; high gain observer; mechanical braking torque generation; physically scaled hybrid duty truck; powertrain structure; regenerative braking; wheel speed measurement; Equations; Feedforward neural networks; Gears; Mathematical model; Torque; Vehicles; Wheels;
Conference_Titel :
American Control Conference (ACC), 2012
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4577-1095-7
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2012.6315003