Haiyan Zhao

A Reduced-Order Nonlinear Clutch Pressure Observer for Automatic Transmission

For a novel type of automatic transmissions adopting clutch-to-clutch shift control technology with electro-hydraulic actuators, a clutch pressure observer method based on input-to-state stability (ISS) is proposed. Model uncertainties including steady state error and unmodelled dynamics are considered as additional disturbance inputs and the observer is designed in order that the error dynamics is input-to-state stable. Lookup tables, which are widely used to represent complex nonlinear characteristics of engine systems, appear in their original form in the designed reduced-order observer. The designed pressure observer is tested on an AMESim powertrain simulation model. Comparing with the sliding mode method, the designed pressure observer has the better performance.

Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method

Abstract To improve the vehicle stability of an electric vehicle with four in-wheel motors, an integrated control scheme with active front wheel steering and direct yaw moment is proposed using a triple-step nonlinear method. The method handles the nonlinear tire characteristics explicitly and actualizes a decoupling control for the considered two-input two-output nonlinear system, in the sense that the closed-loop error dynamics evolve independently. The design procedure is formalized as a triple-step deduction, and the derived controller consists of three parts: steady-state-like control, feedforward control considering reference variations, and state-dependent error feedback control. Finally, the designed controller is evaluated in a realistic seven DOF vehicle model and results are satisfying.

A reduced-order nonlinear clutch pressure observer for automatic transmission using ISS

For a new kind of automatic transmissions using proportional pressure valves to control the clutches directly, a clutch pressure observer design method is suggested in the concept of input-to-state stability (ISS). Model uncertainties including steady state errors and unmodelled dynamics are considered as additive disturbance inputs and the observer is designed such that the error dynamics is input-to-state stable. Lookup tables, which are widely used to represent complex nonlinear characteristics of engine systems, appear in their original form in the designed reduced-order observer. Finally, the designed pressure observer is tested on an AMESim powertrain simulation model.

Slip ratio estimation for electric vehicle with in-wheel motors based on EKF without detection of vehicle velocity

It is necessary to detect vehicle speed to calculate the slip ratio in slip control systems. However, it is hardly to measure the vehicle speed directly for electric vehicle (EV) with in-wheel motors. So, this paper proposed a new slip ratio estimation method for EV with in-wheel motors based on Extended Kalman Filter (EKF) without detecting the vehicle speed. This method takes advantage of the features of driving motors to directly estimate the slip ratio of four wheels at the same time without detecting vehicle speed. First, according to the measurable torque and rotate speed of four wheels, deduce the estimating equations without the vehicle speed. Then, apply the EKF algorithm to design the slip ratio estimator, the EKF can effectively deal with the non-linear control problem and can easily synchronous processing with high performance. Finally, the good performance of the proposed estimator is confirmed by running the electric vehicle model with four in-wheel motors through several test maneuvers.