Bingzhao Gao

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.

Position Control of Electric Clutch Actuator Using a Triple-Step Nonlinear Method

For a novel electric clutch actuator, a nonlinear feedforward-feedback control scheme is proposed to improve the performance of the position tracking control. The design procedure is formalized as a triple-step deduction, and the derived controller consists of three parts: steady-state-like control; feedforward control based on reference dynamics; and state-dependent feedback control. The structure of the proposed nonlinear controller is concise and is also comparable to those widely used in modern automotive control. Finally, the designed controller is evaluated through simulations and experimental tests, which show that the proposed controller satisfied the control requirement. Comparison with proportional-integral-derivative control is given as well.

Automotive Control: the State of the Art and Perspective

Abstract Automotive control technology plays a significant role for the sustainable development of auto-industry. Under gradually fierce circumstance of competition around the world, how to strengthen our capacity of independent research and development of auto-control technology through the innovation of theory and method presents a grand challenge of our time. This paper introduces the state of the art of automotive control focusing on the power-train control, active safety control and new energy vehicle control, then summarizes their common problems and finally puts forward a series of perspective for the future researches.

Observer-based clutch disengagement control during gear shift process of automated manual transmission

A clutch disengagement strategy is proposed for the shift control of automated manual transmissions. The control strategy is based on a drive shaft torque observer. With the estimated drive shaft torque, the clutch can be disengaged as fast as possible without large driveline oscillations, which contributes to the reduction of total shift time and shift shock. The proposed control strategy is tested on a complete powertrain simulation model. It is verified that the system is robust to the variations of driving conditions, such as vehicle mass and road grade. It is also demonstrated that the revised system with switched gain can provide satisfactory performance even under large estimation error of the engine torque.

Data-Driven Predictive Gearshift Control for Dual-Clutch Transmissions and FPGA Implementation

During the gearshift management process, the shift time and the shift shock affect the shift quality (smoothness and efficiency) greatly. In this paper, a gearshift controller is designed using a data-driven predictive control technique to improve the shift quality of vehicles with a dual-clutch transmission (DCT). It is directly obtained from the input-output data of a DCT model constructed by the commercial software AMESim. In order to obtain an offset-free control for the reference input, a predictor equation is gained with the incremental input and outputs. The conflicting control requirements of a short shift time and a small shift shock are taken into account in the optimal objective function by smoothly tracking a selected proper reference trajectory and limiting the change rate of the actuator. Moreover, due to physical characteristics, the constraints of the actuator are explicitly considered in the problem formulation. Finally, the effectiveness of the proposed data-driven predictive controller is tested in the AMESim simulation model of a DCT vehicle. Aiming to pursue a real-time improvement of the hardware computing speed for the data-driven predictive controller, a novel scheme for implementing the designed controller based on a field-programmable gate array (FPGA) is proposed. Moreover, a rapid prototyping platform based on an FPGA and dSPACE is introduced for testing and verifying the computational performance of the proposed controller. The experimental results show that the designed gearshift control algorithm for gearshift has better performance in real time, and the control performance can be guaranteed in a real-time environment.

Nonlinear feedforward–feedback control of clutch-to-clutch shift technique

To improve the shift quality of the vehicle with clutch-to-clutch gear shifts, a nonlinear feedforward–feedback control scheme is proposed for clutch slip control during the shift inertia phase. The feedforward control is designed based on flatness in consideration of the system nonlinearities, and the linear feedback control is given to accommodate the model errors and the disturbances. Lookup tables, which are widely used to represent complex nonlinear characteristics of powertrain systems, appear in their original form in the designed feedforward controller, while the linear feedback controller is calculated through linear matrix inequalities such that the control system is robust against the parameter uncertainties. Finally, the designed controller is tested on an AMESim powertrain simulation model, which contains a time-variant model of clutch actuators.

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.

Design of a Data-Driven Predictive Controller for Start-up Process of AMT Vehicles

In this paper, a data-driven predictive controller is designed for the start-up process of vehicles with automated manual transmissions (AMTs). It is obtained directly from the input-output data of a driveline simulation model constructed by the commercial software AMESim. In order to obtain offset-free control for the reference input, the predictor equation is gained with incremental inputs and outputs. Because of the physical characteristics, the input and output constraints are considered explicitly in the problem formulation. The contradictory requirements of less friction losses and less driveline shock are included in the objective function. The designed controller is tested under nominal conditions and changed conditions. The simulation results show that, during the start-up process, the AMT clutch with the proposed controller works very well, and the process meets the control objectives: fast clutch lockup time, small friction losses, and the preservation of driver comfort, i.e., smooth acceleration of the vehicle. At the same time, the closed-loop system has the ability to reject uncertainties, such as the vehicle mass and road grade.

Optimal Trajectory Planning of Motor Torque and Clutch Slip Speed for Gear Shift of a Two-Speed Electric Vehicle

In order to improve the shift quality of a 2-speed I-AMT of electric vehicle, optimal control is used to generate the reference trajectories of the clutch slip speed and motor torque. The off-line optimization results are fitted and used for online implementation. In order to compensate the disturbances and modeling errors, a PID controller is added to ensure the closed-loop control performance. The proposed controller is almost free of calibration effort, because the feedforward part of the proposed controller considered the simple but dominant system dynamics. Finally the control algorithm is confirmed through large amounts of tests on a complete power train simulation model, and the designed controller can provide satisfactory performance even under large variation of vehicle mass and road grade.

Data-Driven Design of Parity Space-Based FDI System for AMT Vehicles

Automated manual transmission (AMT) and its automatic shifting accuracy play a significant role in driveline performance and reliability of vehicles. Consisting of an engine, a clutch, a gearbox, shafts, and wheels, an AMT system becomes complicated and complex process. Therefore, the fault detection and isolation (FDI) are not easily done and need to be improved. The main contribution of this study is a systematic design of a parity space-based FDI system directly from input-output data. Dynamic cases of faulty occurrence in clutch, engine speed, throttle angle, and three-shaft speed sensors are considered, and the proposed approach is shown to be successful in each case.