Electronic stability control (ESC) is an evolution of antilock brake technology designed to help drivers maintain control of their vehicles in high-speed or sudden maneuvers and on slippery roads. Manufacturers first began equipping vehicles with ESC in the mid 1990s in Europe, and the technology appeared in other markets several years later. The wider proliferation of ESC across the vehicle fleet has allowed evaluation of its effects in real world crashes in many countries, including Japan, Germany, Sweden, France, Great Britain, and the United States. Studies have examined crash effects on different roadways, using differing analytic methods, different crash severities, and different make/model vehicles including both cars and SUVs. This paper provides a summary of those findings. Most studies find that ESC is highly effective in reducing single-vehicle crashes in cars and SUVs. Fatal single-vehicle crashes involving cars are reduced by about 30-50 percent and SUVs by 50-70 percent. Fatal rollover crashes are estimated to be about 70-90 percent lower with ESC regardless of vehicle type. A number of studies find improved effectiveness in reducing crashes when road conditions are slippery. There is little or no effect of ESC in all multi-vehicle crashes; however, there is a 17-38 percent reduction in more serious, fatal multi-vehicle crashes. Given the extraordinary benefits of ESC in preventing crashes, the implementation of ESC should be accelerated to include the full range of vehicles in both developed and developing markets.

The effectivness of electronic stability control in reducing real world crashes: a literature review

To improve the stability of the autonomous vehicle for high speed tracking, a vehicle estimator scheme integrated into a path-tracking system has been proposed in this paper. Vehicle stability is r...

Path-tracking of an autonomous vehicle via model predictive control and nonlinear filtering:

This study designs an adaptive integrated control. The control system includes two strategies of individual optimal linear quadratic regulator: one to improve vehicle maneuverability and another to improve vehicle stability. The integration is based on the vehicle dynamic variables in the phase plane. The controller can adapt itself by changing gains and integration law as vehicle mass and road friction change. The proper gains and integration law are determined for four special conditions: dry road-curb weight, dry road-gross weight, wet road-curb weight, and wet road-gross weight. These conditions are then expanded for every value of vehicle mass and road friction through fuzzy logic and Sugeno estimator. Simulation results show that considerable improvements are achieved in vehicle dynamic performance through the adaptive integrated control system.

Adaptive integrated control design for vehicle dynamics using phase-plane analysis †

Yaw stability control system helps vehicle to improve the cornering performance during high speed. There are two control objective for improving yaw control performance i.e. yaw rate and side slip angle. The main aim of yaw stability demand to get appropriate yaw rate maintaining side slip angle during cornering. The loss of yaw stability results in oversteer and understeer phenomena which is undesirable. In this paper first a seven-DOF vehicle is linearized to a bicycle model. Three different industrial control strategy i.e. Active steering with PID control, Active steering with fractional PID control and an optimal control based Linear Quadratic regulator (LQR) is used for maintaining yaw stability. In order to evaluate the robustness of the controller variation of road condition is taken care of. For testing vehicle in realtime scenario it is tested with two different road maneuver. The complete design of simulation model is done in matlab environment.

A comparative study of different yaw stability control strategies with different road condition and handling maneuver

In this paper, the hub motor driven pure electric vehicle as a prototype, side-slip angle and angular velocity as a controlled variable to design a path tracking controller based on adaptive terminal sliding mode. Through the simulation it can be the design of the adaptive control method based on terminal sliding mode can ensure the vehicle driver's action in 1s after completion of rapid response operation and maintain the stability of the vehicle, and angular velocity and side-slip angle can be very good with the ideal value, to ensure the stability of vehicles and comfort.

Stability control of hub motor driven pure electric vehicle

An 8-dof vehicle nonlinear dynamic model was established with the linear 2-dof vehicle handling characteristics model as the target control. The vehicle stability control system yaw and yaw rate combined fuzzy control simulation model was established based on automobile yaw moment and vehicle state deviation between the dynamic relationship. Through the hook simulation test, which shows that the active yaw control system can make the vehicle steadily drive.

Huigang Wang

Papers

Fuzzy control for vehicle stability