Identification and Control of Electronic Throttle Drive
Master2003The electronic throttle (or throttle-by-wire) is a DC servo-drive which controls the airflow into the intake manifold of the spark-ignited automotive engine. In this thesis an adaptive digital position control system for an automotive electronic throttle body (ETB) is designed. The proposed control strategy is implemented and examined by computer simulation and experimentally on the experimental setup of the electronic throttle control system.
Detailed off-line experimental identification of the electronic throttle body is carried out with the aim to determine the parameters of ETB model and to aid the design of a high performance electronic throttle control strategy. The linear and nonlinear parts of the electronic throttle process model are conveniently identified separately. Identification of linear ETB dynamics includes a multi-step identification method based on physical ETB model form, and single-step methods based on black-box continuous integral+lag (IT1) model and discrete-time ARX process model. The nonlinear effects identified include different static and dynamic friction effects, and distinctive limp-home nonlinearity of the dual return spring.
A linear PID feedback throttle position controller is algebraically optimized according to the damping optimum. The PID controller is tuned to provide critically damped (aperiodic) response of the throttle position control loop. In order to deal with different parameters of the linear process model for the regions below and above the limp-home position, a PID controller gain-scheduling algorithm is applied. The proposed feedback controller is extended with a feed-forward controller placed in the position reference path, in order to obtain faster throttle reference response.
Transmission friction and return spring limp-home nonlinearity affect the performance of the electronic throttle servosystem. The influence of these effects is analyzed by means of computer simulation and experiment. A novel friction model is developed, in order to adequately capture the experimentally observed characteristics of the presliding displacement and breakaway effects. In order to deal with the undesirable nonlinear effects of friction and limp-home nonlinearities, the linear feedback/feed-forward controller is extended with nonlinear feedback friction and limp-home feedback compensators.
The electronic throttle body parameters can significantly vary due to production deviations, variations of external conditions (e.g. temperature), and aging. In order to avoid the influence of these relatively slow ETB parameters variations to the performance of electronic throttle control system, an electronic throttle auto-tuning is introduced. The auto-tuner tunes the parameters of the electronic throttle control strategy based on the results of on-line identification of linear and non-linear process dynamics. The auto-tuner is accurate, fast, and easy to implement. In addition, it does not require any prior knowledge of ETB process parameters. The proposed auto-tuning algorithm can be executed only once in the stage of vehicle production, or frequently at the end of each engine cycle.
A self-tuning strategy for the electronic throttle control system is proposed in order to account for the variations of armature resistance, battery voltage and limp-home position, which may occur within a single engine run. The self-tuning algorithm is based on the on-line estimation of process parameters. Different self-tuning algorithms have been derived depending on the availability of armature current sensor and control strategy auto-tuning procedure. The proposed self-tuning strategy is accurate and has simple structure, which makes it easy to implement on a low-cost microcontroller system. For the purpose of experimental verification, a real-time simulator of process parameters variations is developed. electronic throttle; DC drive; dual return spring; friction; limp-home nonlinearity; process identification; analysis; modeling; position control; PID controller; feed-forward controller; damping optimum; friction and limp-home compensation; auto-tuningv self-tuning
Master
2003