Search Results

Nowadays, electric control steering system has been a main tendency. It consists of Electric Power Steering (EPS) system, Steer by Wire (SBW) system and Active Front Steering (AFS) system. EPS is more widely applied and its technology is more developed. By 2010, the cars equipped with EPS have reached almost 30%. This paper describes one integrated test bench which can test and verify electric control steering system. The main target of the paper is to design and set up a resistance loading system for the test bench referred. The paper takes EPS as a prototype to verify the designed resistance loading system. If the resistance loading system provides a precise simulated torque for the bench, the results of tests will be more approximate with vehicle tests and the acquired data will be reliable for electric control steering system's design and improvement. The linear electric cylinder applied in the loading system is used to provide simulated torque for the bench.

The paper describes an algorithm, which estimates the mass of large buses and axle load distribution using pedal position, wheel speed and the wheel cylinder pressure sensors. This algorithm is allowed to achieve the purpose without additional sensors by using the rotational speed sensors from ABS system and air pressure sensors in brake cylinders form ESP system. The axle load distribution algorithm mainly consists of three steps. Firstly, deceleration of the bus is estimated and then the mass of the bus is estimated. After that, the position of the mass centre is estimated. Taking account of the tire nonlinear characteristics under longitudinal forces and vertical forces, mass estimation, deceleration and the position of the mass centre of buses is corrected by the coefficient, which is determined by the wheel cylinder pressure, the wheel speed and mass estimation.

This paper first presents an algorithm to detect tire blowout based on wheel speed sensor signals, which either reduces the cost for a TPMS or provides a backup in case it fails, and a tire blowout model considering different tire pressure is also built based on the UniTire model. The vehicle dynamic model uses commercial software CarSim. After detecting tire blowout, the active braking control, based on a 2DOF reference model, determines an optimal correcting yaw moment and the braking forces that slow down and stop the vehicle, based on a linear quadratic regulator. Then the braking force commands are further translated into target pressure command for each wheel cylinder to ensure the target braking forces are generated. Some simulations are conducted to verify the active control strategy.