Electronic Throttle Control System Research Articles

Modeling and Tuning of Electronic Throttle Control System in Formula Student Car

The Lookprabida formula student team uses an electronic throttle control (ETC) system in the racecar. Unfortunately, the ETC system cannot regulate the throttle valve to closely pursue angular setpoints. Thus, this paper endeavors to improve the response of the ETC system in racing cars. The ETC system is first examined using frequency response analysis. Parameter identification is carried out to obtain a mathematical model for the electronic throttle body. The Ziegler-Nichols’ second method is then applied to preliminarily select the proportional integral derivative (PID) gains using MATLAB/Simulink®. Then, the ETC system fine-tuning on the experimental set is carried out. The final PID controller design results in a reduction in the settling time from 0.35 to 0.20 s, overshoot from 29.6 to 19.33%, and steady-state error from 2.00 to 0.22%. The racecar with the finally designed PID gains is tested on a training track; the root mean square error (RMSE) shows that the throttle valve approaches much closer to angular setpoints.

Self-Tuning Backstepping Control with Kalman-like Filter for High-Precision Control of Automotive Electronic Throttle

The automotive electronic throttle (AET) control system has been widely applied in modern automotive engines, and accurate control of AET can improve engine performance as well as reduce pollution emissions. However, the noise in the sensor circuit and the variation in automotive driving conditions seriously affect the control performance of the AET system, making controller designing challenging. This paper proposes a self-tuning backstepping control with a Kalman-like filter (SBCKLF) strategy. First, the noise affecting the position sensor measurement is verified to be non-Gaussian by acquiring and processing the noise signal. To eliminate its influence on control precision, a Kalman-like filter is introduced to estimate the real position of the valve. Then, a self-tuning backstepping controller is designed to automatically adapt to the variation in vehicle driving conditions. A self-tuning algorithm based on fuzzy control is used to tune the parameters of the backstepping controller online, so as to optimize the controller performance. Finally, an experimental platform based on dSPACE for the AET control system is built to perform the controller comprehensive test in a real-time environment. Experimental results and performance analysis demonstrate the effectiveness of the proposed SBCKLF strategy. Compared to the best results of other methods, the proposed method reduces the maximum and root mean square tracking errors by 21.65% and the average error by 12.89%. The steady-state and tracking error bounds are controlled to 0.9° and 2.3°, respectively. It also shows that the SBCKLF strategy has the strongest robustness as well as the best response speed.

A Novel Adaptive Control Scheme for Automotive Electronic Throttle Based on Extremum Seeking

To achieve rapid and high-precision servo control of an electronic throttle, an adaptive control scheme is proposed based on the extremum seeking (ES), which consists of a variable-gain adaptive proportional-integral (ES-API) controller and an adaptive compensator (ES-ACP). The two gains ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K_p}$</tex-math> </inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K_i}$</tex-math> </inline-formula> ) of the ES-API controller are designed as maps with respect to the tracking error, and the parameters of these maps are learned by ES. Additionally, the ES-ACP is applied to compensate for the strong nonlinearity inherent in an electronic throttle control (ETC) system, whose parameters are also learned by ES. During parameter learning, an objective function is utilized to quantify the tracking error of the opening angle of the electronic throttle plate, and then the parameters are learned using a step reference signal and a ramp reference signal. ES optimizes the above parameters by reducing the objective function to achieve a more favorable tracking response. Five reference signals are used to evaluate the learned controller after the parameter learning process is completed. Experiments were performed on a test bench equipped with an electronic throttle, and the experimental results show that the control scheme is capable of tracking multiple reference trajectories quickly and accurately.

SMC for Discrete-Time Networked Semi-Markovian Switching Systems With Random DoS Attacks and Applications

This article concentrates on the discrete-time sliding mode control (DTSMC) problem for uncertain networked semi-Markovian switching systems (S-MSSs) under random denial-of-service (DoS) attacks. The semi-Markovian kernel (SMK) approach is utilized such that the switching among different modes is mutually governed by the transition probability and the sojourn-time distribution function. Considering randomly occurring DoS attacks, a sliding mode function related to the attack probability is constructed to analyze the impact of malicious attacks. Then, sufficient conditions under the equivalent DTSMC law are derived in view of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula> -error mean square stability criterion. Furthermore, the synthesis problem of the proposed DTSMC law ensures that the resulting closed-loop system dynamics can be driven onto the prespecified sliding region within a limited time. Finally, an electronic throttle control system is shown to validate the proposed algorithm.

Adaptive constrained control for automotive electronic throttle control system with experimental analysis

Abstract This article proposes an adaptive constrained control strategy with state constraints and uncertain parameters for an electronic throttle control (ETC) system. Compared with the current control strategies for an ETC system, state constraints and parameter uncertainties are adequately considered in the proposed control strategy. First, the nonlinear dynamic model for control of an ETC is described. Second, the asymmetric Barrier Lyapunov Function (BLF) and a backstepping control algorithm are used to ensure that the throttle opening does not exceed the constrained boundary. A parameter adaptive law is given to estimate the unknown parameter and external disturbances with an ETC system. Third, the proposed BLF controller is compared with the existing Quadratic Lyapunov Function (QLF) controller by simulation and experiment. The results show that the proposed control algorithm not only ensure fast transient performance in the control response, but also avoid the out of bounds of the throttle opening. The proposed constrained control strategy can provide excellent control performance for an ETC system.

Barrier Lyapunov Function-Based Adaptive Back-Stepping Control for Electronic Throttle Control System

This paper presents an adaptive constraint control approach for Electronic Throttle Control System (ETCS) with asymmetric throttle angle constraints. The adaptive constraint control method, which is based on barrier Lyapunov function (BLF), is designed not only to track the desired throttle angle but also to guarantee no violation on the throttle angle constraints. An ETC mathematic model with complex non-linear system is considered and the asymmetric barrier Lyapunov function (ABLF) is introduced into the design of the controller. Based on Lyapunov stability theory, it can be concluded that the proposed controller can guarantee the stability of the whole system and uniformly converge the state error to track the desired throttle angle. The results of simulations show that the proposed controller can ensure that there is no violation on the throttle angle constraints.

Design, implementation and experimental verification of a compensator-based triple-step model reference controller for an automotive electronic throttle

The electronic throttle of a gasoline vehicle controls the air inflow into the cylinders of the engine to ensure the desired power output. Therefore, a well-established electronic throttle control (ETC) system is fundamental and necessary to obtain fast transient engine torque responses without overshoot and with high static precision. To achieve highly precise servo control of the throttle in an environment with system nonlinearity, model uncertainties and external disturbances, a discrete-time triple-step model reference controller (DT-TSMRC) with an adaptive compensator is proposed for an ETC system. In contrast to previously investigated systems, the proposed controller consists of steady-state control, reference feedforward control, proportional-derivative (PD)-type feedback control, and an online updating compensation law. Experimental results show that the proposed control algorithm can not only ensure fast transient performance in the control response without overshoot but also guarantee accurate servo tracking of the valve plate angle.

Adaptive prescribed performance servo control of an automotive electronicthrottle system with actuator constraint

To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can enhance the robustness of the transient and steady-state performance against uncertainty from the product tolerance, the operating conditions, and the aging of components. Both Matlab/Simulink simulation and dSPACE-based hardware-in-the-loop experimental verification show the effectiveness and applicability of the proposed control strategy.

Immune Feedback Strategy in an Electronic Throttle Control System

The control strategy for improving the emission performance of engine transition condition is explored to enhance the dynamic response characteristics of the electronic throttle control system of automobile engines. A strong nonlinear relationship exists among the return spring, gear backlash, throttle shaft, and throttle body friction of the electronic throttle electromechanical system, thereby affecting the dynamic response characteristics of the engine electronic throttle under various operating conditions. On the basis of the nonlinear electronic throttle electromechanical system, a corresponding mathematical model is established to study the electronic throttle control system. Then, fuzzy and immune feedback control algorithms are applied to the motion control of the electronic throttle system on the basis of intelligent control because of its advantages of strong anti-disturbance ability, strong robustness, and applicability to nonlinear control systems. The immune feedback control algorithm is characterized by a rapid response in the control system. The influence of nonlinearity of the electronic throttle system on the control effect is discussed in this paper. The fuzzy immune PID controller is designed on the basis of the classical control algorithm PID for control precision and response of the system. The fuzzy control algorithm's adaptability to the nonlinear system improves the response performance of the electronic throttle system, and the immune feedback algorithm enhances the response efficiency of the control system. The response characteristics of electronic throttle is further explored. Experimental results show that the response speed of the fuzzy immune PID control system and speed adjustment of the dynamic characteristics of indicators have clear advantages over those of the PID and fuzzy PID control system. The controller is conducive to the improvement of the electronic throttle response characteristics. Improving the power, economy, and emissions of vehicles has important significance.

A Brawny hybrid FOFPID in MODA controller in HEVs

ABSTRACTControl system is the vital integrant in proportional–integral–derivative (PID) controller. The controllers are also planted in many special-purpose control systems. PID controller is often combined with logic, sequential functions, selectors, and simple function blocks to build the complicated automation systems used for energy production, transportation, and manufacturing. In the existing process, PID controller controls water level, speed, temperature, etc. Some of the issues arise while using PID controller can be easily solved by integrating fuzzy or with some other soft computing techniques. The major difficulty in PID controller is feedback system, with constant parameters and no direct knowledge of the process. Our proposed methodology has been introduced to control the speed of highly nonlinear hybrid electric vehicles (HEVs) having an electronic throttle control system in the cascade control loop. In recent PID controllers, no such specific tuning methods are applicable. The proposed method uses fractional order fuzzy PID nonlinear controller that is used in the cascade control loop. Aging leader and challenger-aided multi-objective dragonfly algorithm is considered for controller optimization in closed loop. It is employed to enhance the gain of the controller for the reduction of integral absolute error, maximum overshoot, settling time elimination of disturbance, uncertainty model, and control HEVs.

Adaptive finite time servo control for automotive electronic throttle with experimental analysis

In order to meet the rigorous requirement for transient and static performance of automobile electronic throttle control systems, an adaptive finite time servo control (AFTSC) strategy is investigated by integrating adaptive backstepping recursive technique into the framework of finite-time stability theory. The required transient performance of the throttle opening trajectory tracking is guaranteed theoretically by the finite convergence time and the convergence rate related to the adjustable control parameters. The static performance is enhanced by introducing the tracking error integral into the system state variables. The robustness of the satisfactory transient and static performance is improved by the adaptive update law in the light of system parameter uncertainties due to production deviations, different working conditions and aging. Meanwhile, the advantage of the proposed AFTSC strategy is validated by demonstrating the comparison results with the existing strategies both in the critical operating cases under Matlab/Simulink simulation environment and in the actual operating cases on the dSPACE rapid-control-prototype (RCP) test platform for a real electronic throttle system.

A Fuzzy Approach for Optimal Robust Control Design of an Automotive Electronic Throttle System

In this paper, we propose a fuzzy approach for optimal robust control design of an automotive electronic throttle (ET) system. Compared with the conventional ET control systems, we establish the fuzzy dynamical model of the ET system with parameter uncertainties, nonlinearities, and external disturbances, which may be nonlinear, (possibly fast) time varying. These uncertainties are assumed to be bounded, and the knowledge of the bound only lies within a prescribed fuzzy set. A robust control that is deterministic and is not the usual if–then rules-based control is presented to guarantee the controlled system to achieve the deterministic performance: uniform boundedness and uniform ultimate boundedness. Furthermore, a fuzzy-based system performance index including average fuzzy system performance and control cost is proposed based on the fuzzy information. The optimal design problem associated with the control can then be solved by minimizing the fuzzy-based performance index. With this optimal robust control, the performance of the fuzzy ET system is both deterministically guaranteed and fuzzily optimized.

ESO-Based Double Closed-loop Servo Control for Automobile Electronic Throttle

A kind of double closed-loop servo control strategy is presented in this paper to realize accurate and fast position tracking of throttle valve for the automobile electronic throttle control system (ETCS). The control structure includes an extended state observer (ESO) compensating for the total disturbances resulted from nonlinearities of friction and return springs and uncertainties of some physical parameters, and two PI-type controllers with disturbance compensators of the outer position loop and the inner current loop. The proposed scheme is featured by transforming the control gains determination for the two PID-type controllers into the derivation of state feedback gains. And the transformation is carried on by means of the augmented deviation equations constructed by the ESO-estimated unmeasurable current and angular velocity of throttle. And control parameters of the two feedback loop controllers and ESO can be instructively determined by solving the linear matrix inequalities (LMIs) obtained from the Lyapunov stability analysis of the whole closed-loop system. The feasibility of the proposed strategy is validated in both simulation and hardware-in-the loop (HIL) test platform.

Extended state observer–based intelligent double integral sliding mode control of electronic throttle valve

Motivated by achieving precise positioning of the throttle plate, an extended state observer–based intelligent double integral sliding mode control strategy is proposed for the electronic throttle control system. Specifically, an extended state observer is first designed to observe the opening angle change of the electronic throttle and compensate unexpected external disturbance. On this basis, an intelligent double integral sliding mode controller for electronic throttle valve is presented based on Lyapunov stability theory and sliding mode control theory, which includes stability analysis and parameter adaptation design. Finally, extensive simulations are conducted to demonstrate the superior performance of the proposed method.

Synthesis and validation of finite time servo control with PSO identification for automotive electronic throttle

In order to enhance the rapidity and accuracy of throttle opening trajectory tracking for vehicle electronic throttle control (ETC) systems, a finite time servo control strategy is investigated by incorporating the particle swarm optimization (PSO) identification technique with the finite time stability theory. The PSO technique is adopted to identify the uncertain physical parameters of a real vehicle ETC system. In the PSO-based identification algorithm, the integrated square error between the actual and model throttle opening angles is regarded as the fitness function, and the mutation operation is added to prevent the particles from falling into local optimum. The designed servo controller is comprised of a feed-forward controller for trajectory tracking accuracy, a nonlinearity compensator for friction and return spring, and a feedback controller for finite time stability by utilizing additional power integrator and backstepping technique. The effectiveness of the proposed control strategy is verified by both the comparison results with the existing strategy in MATLAB/Simulink environment and the experiment results carried out on the electronic throttle hardware-in-loop test platform in several actual operating cases.

Model-Based Control for Mode Transition Between Spark Ignition and HCCI Combustion

While the homogeneous charge compression ignition (HCCI) combustion has its advantages of high thermal efficiency with low emissions, its operational range is limited in both engine speed and load. To utilize the advantage of the HCCI combustion, an HCCI capable spark ignition (SI) engine is required. One of the key challenges of developing such an engine is to achieve smooth mode transition between SI and HCCI combustion, where the in-cylinder thermal and charge mixture properties are quite different due to the distinct combustion characteristics. In this paper, a control strategy for smooth mode transition between SI and HCCI combustion is developed and experimentally validated for an HCCI capable SI engine equipped with electrical variable valve timing (EVVT) systems, dual-lift valves, and electronic throttle control (ETC) system. During the mode transition, the intake manifold air pressure is controlled by tracking the desired throttle position updated cycle-by-cycle; and an iterative learning fuel mass controller, combined with sensitivity-based compensation, is used to manage the engine torque in terms of net mean effective pressure (NMEP) at the desired level for smooth mode transition. Note that the NMEP is directly correlated to the engine output torque. Experiment results show that the developed controller is able to achieve smooth combustion mode transition, where the NMEP fluctuation is kept below 3.8% during the mode transition.

An Integrated Pedal Follower and Torque Based Approach for Electronic Throttle Control in a Motorcycle Engine

Nowadays, electronic throttle control system is widely adapted in the motorcycle for better drivability, fuel economy and reduces the emissions. In such systems, pedal follower or torque based approach are used for calculating the required throttle angle for the given torque demand by driver. This work presents a throttle control system for the precise estimation of throttle angle based on the integrated pedal follower and torque based approach for the given accelerator position and torque demand by the driver. A mathematical model for an electronic throttle body is developed to understand the effects of nonlinearities due to friction and limp home dual springs. A PID controller with compensators are developed to handle the nonlinearities due to the friction and limp home dual springs in the proposed electronic throttle control system. A simulation study has been carried out using software in loop and hardware in loop simulation approaches for step, sinusoidal, and ramp input signals. The responses of electronic throttle body for opening the throttle angle and error are analyzed for the given input signals. The simulation result shows that the proposed compensators has significant advantage in reducing the throttle angle error and gives the desired output.

Design and Implementation of Electronic Throttle Control System Based on MotoHawk

This paper introduces the rapid prototyping technology of electronic throttle system based on MotoHawk platform. It builds the mathematical model of the electronic throttle, then designs and verifies incremental PID controller algorithm in Matlab/Simulink. Using MotoTron company's advanced technology to set up electronic throttle development platform. Through transplanting strategy and the calibration test after downloading finally realizes the optimization of control performance.

Experimental study for the reproduction of sudden unintended acceleration incidents

A few cases of the sudden unintended acceleration have been reported over the last few years [1–11] and some of them seemed to be somewhat related to an electronic throttle control (ETC) system [11,12]. In this experimental study, efforts were made to reproduce the cases of sudden unintended acceleration possibly related to the ETC. Typically, an ETC of the engine is managed based on signals from airflow sensor, throttle position sensor and acceleration pedal sensor. With this typical sensor configuration in mind, these sensor signals were checked for noise levels. However, none of them showed any clear relationship with the sudden unintended acceleration mainly due to the robustness of the ETC logic software. As an alternative approach, supply voltage to an engine control unit (ECU) was tempered intentionally to observe any clues for the incidents. The observed results with the supply voltage drop and fluctuation tests were rather astonishing. The throttle valve position went all the way up to 100% for around one second when the battery voltage plunged down to 7V periodically despite that the acceleration pedal position was kept steady. As an effort to confirm the case, multiple tries were made systematically on a chassis dynamometer as well as on the test road. In this paper, detailed procedures and findings are reported accordingly.

Neural network-based fuzzy inference system for speed control of heavy duty vehicles with electronic throttle control system

The objective of this study is to apply various control approaches to control the speed of a heavy duty vehicle using an electronic throttle control system. However, the DC servo motor is used for controlling the angular position of electronic throttle valve. Moreover, four control techniques are used to control prescribed two different random inputs of the heavy duty vehicle speed. These control structures are named as standard PID controller, model-based neural network controller, adaptive neural network-based fuzzy inference controller and proposed robust adaptive neural-based fuzzy inference control systems. On the other hand, the time performance specifications such as rise time, settling time, peak time, peak value and steady-state error are also examined for these control approaches. The results of the simulation for four approaches showed that the proposed robust adaptive neural network-based fuzzy inference control system has better performance rather than other standard control systems under varying speed conditions. Finally, the proposed control system structure will be implemented for speed control of DC servo motor.