A comparison on optimal torque vectoring strategies in overall performance enhancement of a passenger car

2016 ◽  
Vol 230 (4) ◽  
pp. 469-488 ◽  
Author(s):  
Seyed Mohammad Mehdi Jaafari ◽  
Kourosh Heidari Shirazi
Keyword(s):  
Fuel Consumption ◽  
Ride Comfort ◽  
Stability Control ◽  
Electronic Stability Control ◽  
Slip Angle ◽  
Vehicle Model ◽  
Side Slip Angle ◽  
Wheel Drive ◽  
Torque Vectoring ◽  
Four Wheel Drive

In this paper, a comparison is made on different torque vectoring strategies to find the best strategy in terms of improving handling, fuel consumption, stability and ride comfort performances. The torque vectoring differential strategies include superposition clutch, stationary clutch, four-wheel drive and electronic stability control. The torque vectoring differentials are implemented on an eight-DOF vehicle model and controlled using optimized fuzzy-based controllers. The vehicle model assisted with the Pacejka tyre model, an eight-cylinder dynamic model for engine, and a five-speed transmission system. Bee’s Algorithm is employed to optimize the fuzzy controller to ensure each torque vectoring differential works in its best state. The controller actuates the electronic clutches of the torque vectoring differential to minimize the yaw rate error and limiting the side-slip angle in stability region. To estimate side-slip angle and cornering stiffness, a combined observer is designed based on full order observer and recursive least square method. To validate the results, a realistic car model is built in Carsim package. The final model is tested using a co-simulation between Matlab and Carsim. According to the results, the torque vectoring differential shows better handling compared to electronic stability control, while electronic stability control is more effective in improving the stability in critical situation. Among the torque vectoring differential strategies, stationary clutch in handling and four-wheel drive in fuel consumption as well as ride comfort have better operation and more enhancements.

Torque-vectoring stability control of a four wheel drive electric vehicle

2015 ◽  
Author(s):  
Benedict Jager ◽  
Peter Neugebauer ◽  
Reiner Kriesten ◽  
Nejila Parspour ◽  
Christian Gutenkunst
Keyword(s):  
Electric Vehicle ◽  
Stability Control ◽  
Wheel Drive ◽  
Torque Vectoring ◽  
Four Wheel Drive

Stability Optimal Control Based on 15-Dof Vehicle Model

2011 ◽  
Vol 299-300 ◽  
pp. 1266-1270 ◽  
Author(s):  
Xiao Bin Fan ◽  
Yu Jiang ◽  
Hui Gang Wang
Keyword(s):  
Control System ◽  
Estimation Algorithm ◽  
Stability Control ◽  
Slip Angle ◽  
Vehicle Model ◽  
Simulation Test ◽  
Side Slip Angle ◽  
Handling Characteristics ◽  
Stability Control System ◽  
The Stability

The 15 degrees of nonlinear dynamic vehicle model is established, and then Dugoff and magic formula tire model are studied by comparison. Then the braking system dynamics model and the side-slip angle estimation algorithm are discussed. Stability control system is established based on the control target of combined yaw and side-slip angle with linear 2-dof vehicle handling characteristics model. It shows that control system can perfectly control vehicle driving and can improve the stability of car active safety through the serpent’s simulation test.

scholarly journals Simulation of Differentials in Four-Wheel Drive Vehicles Using Multibody Dynamics

2011 ◽  
Author(s):  
Geoffrey Virlez ◽  
Olivier Bru¨ls ◽  
Pierre Duysinx ◽  
Nicolas Poulet
Keyword(s):  
Test Bench ◽  
Good Accuracy ◽  
Dynamic Performance ◽  
Nonlinear Finite Element Method ◽  
Vehicle Model ◽  
Contact Conditions ◽  
Flexible Bodies ◽  
Wheel Drive ◽  
Complex Phenomena ◽  
Four Wheel Drive

The dynamic performance of vehicle drivetrains is significantly influenced by differentials which are subjected to complex phenomena. In this paper, detailed models of TORSEN differentials are presented using a flexible multibody simulation approach, based on the nonlinear finite element method. A central and a front TORSEN differential have been studied and the numerical results have been compared with experimental data obtained on test bench. The models are composed of several rigid and flexible bodies mainly constrainted by flexible gear pair joints and contact conditions. The three differentials of a four wheel drive vehicle have been assembled in a full drivetrain in a simplified vehicle model with modeling of driveshafts and tires. These simulations enable to observe the four working modes of the differentials with a good accuracy.

Integrated Vehicle Dynamics Control Via Torque Vectoring Differential and Electronic Stability Control to Improve Vehicle Handling and Stability Performance

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Seyed Mohammad Mehdi Jaafari ◽  
Kourosh Heidari Shirazi
Keyword(s):  
Vehicle Dynamics ◽  
Phase Plane ◽  
Stability Control ◽  
Stable Region ◽  
Electronic Stability Control ◽  
Vehicle Handling ◽  
Matlab Simulink ◽  
Β Phase ◽  
Torque Vectoring ◽  
Chassis Control

This paper proposed a full vehicle state estimation and developed an integrated chassis control by coordinating electronic stability control (ESC) and torque vectoring differential (TVD) systems to improve vehicle handling and stability in all conditions without any interference. For this purpose, an integrated TVD/ESC chassis system has been modeled in Matlab/Simulink and applied into the vehicle dynamics model of the 2003 Ford Expedition in carsim software. TVD is used to improve handling in routine and steady-state driving conditions and ESC is mainly used as the stability controller for emergency maneuvers or when the TVD cannot improve vehicle handling. By the β−β˙ phase plane, vehicle stable region is determined. Inside the reference region, the handling performance and outside the region the vehicle stability has been in question. In order to control the integrated chassis system, a unified controller with three control layers based on fuzzy control strategy, β−β˙ phase plane, longitudinal slip, and road friction coefficient of each tire is designed in Matlab/Simulink. To detect the control parameters, a state estimator is developed based on unscented Kalman filter (UKF). Bees algorithm (BA) is employed to optimize the fuzzy controller. The performance and robustness of the integrated chassis system and designed controller were conformed through routine and extensive simulations. The simulation results via a co-simulation of MATLAB/Simulink and CarSim indicated that the designed integrated ESC/TVD chassis control system could effectively improve handling and stability in all conditions without any interference between subsystems.

Test Results: Vehicle Responses to Simulated Drag Caused by Front Tire Tread Detachment — The Effect of Scrub Radius and Speed

2018 ◽  
Author(s):  
Mark W. Arndt ◽  
Stephen M. Arndt
Keyword(s):  
Lateral Displacement ◽  
Rear Wheel ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Slip Angle ◽  
Yaw Rate ◽  
Wheel Drive ◽  
Steady State Responses ◽  
Four Wheel Drive ◽  
Left Front

The effects of reduced kingpin offset distance at the ground (scrub radius) and speed were evaluated under controlled test conditions simulating front tire tread detachment drag. While driving in a straight line at target speeds of 50, 60, or 70 mph with the steering wheel locked, the drag of a tire tread detachment was simulated by applying the left front brake with a pneumatic actuator. The test vehicle was a 2001 dual rear wheel four-wheel-drive Ford F350 pickup truck with an 11,500 lb. GVWR. The scrub radius was tested at the OEM distance of 125 mm (Δ = 0) and at reduced distances of 49 mm (Δ = −76) and 11 mm (Δ = −114). The average steady state responses at 70 mph with the OEM scrub radius were: steering torque = −24.5 in-lb; slip angle = −3.8 deg; lateral acceleration = −0.47 g; yaw rate = −8.9 deg/sec; lateral displacement after 0.75 seconds = 3.1 ft and lateral displacement after 1.5 seconds = 13.1 ft. At the OEM scrub radius, responses that increased linearly with speed included: slip angle (R2 = 0.84); lateral acceleration (R2 = 0.93); yaw rate (R2 = 0.73) and lateral displacement (R2 = 0.59 and R2 = 0.87, respectively). At the OEM scrub radius, steer torque decreased linearly with speed (R2 = 0.76) and longitudinal acceleration had no linear relationship with speed (R2 = 0.09). At 60 mph and 70 mph for both scrub radius reductions, statistically significant decreases (CI ≥ 95%) occurred in average responses of steer torque, slip angle, lateral acceleration, yaw rate, and lateral displacement. At 50 mph, reducing the OEM scrub radius to 11 mm resulted in statistically significant decreases (CI ≥ 95%) in average responses of steer torque, lateral acceleration, yaw rate and lateral displacement. At 50 mph the average slip angle response decreased (CI = 87%) when the OEM scrub radius was reduced to 11 mm.

Sign in / Sign up

Export Citation Format

Share Document