Idle Speed Control Research Articles

Real time model predictive idle speed control of ultra-lean burn engines: experimental results

AbstractIdle speed control of ultra-lean burn engines continues to be a major focus of automotive engineers owing to the benefits offered in terms of fuel economy and emissions reduction. This paper applies a recently proposed linear time varying model predictive approach for the idle speed control of ultra-lean burn internal combustion engines. Unlike conventional gasoline engines, the approach uses fuel flow as the primary control variable to compensate for sudden fluctuations in engine load resulting in a fuel assisted idle speed control strategy. Simultaneously, the spark angle is maintained at a value so as to yield maximum brake torque while the emissions are reduced to negligibly low levels by constraining the engine operation to ultra-lean burn mode. The technique is demonstrated on an inline prototype 4-litre, 6-cylinder hydrogen fuelled internal combustion engine.

Model Predictive Idle Speed Control: Design, Analysis, and Experimental Evaluation

Idle speed control is a landmark application of feedback control in automotive vehicles that continues to be of significant interest to automotive industry practitioners, since improved idle performance and robustness translate into better fuel economy, emissions and drivability. In this paper, we develop a model predictive control (MPC) strategy for regulating the engine speed to the idle speed set-point by actuating the electronic throttle and the spark timing. The MPC controller coordinates the two actuators according to a specified cost function, while explicitly taking into account constraints on the control and requirements on the acceptable engine speed range, e.g., to avoid engine stalls. Following a process proposed here for the implementation of MPC in automotive applications, an MPC controller is obtained with excellent performance and robustness as demonstrated in actual vehicle tests. In particular, the MPC controller performs better than an existing baseline controller in the vehicle, is robust to changes in operating conditions, and to different types of disturbances. It is also shown that the MPC computational complexity is well within the capability of production electronic control unit and that the improved performance achieved by the MPC controller can translate into fuel economy improvements.

Study of Integral Variable Structure Control Method for Stability of SI Engine Idling Speed

The intake air control system of a gasoline engine is a typical nonlinear system, and included among the adverse fac-tors that always induce poor idle-speed control stability are dead time and disturbances in the intake air control process. In this paper, to improve the responsiveness when idling with regard to disturbances, a mean-value engine model (MVEM) with dead time was constructed as the control object, and the two servo structures of sliding mode control (SMC) were studied for better idle control performance, especially in transient process of speed change. The simulation results confirmed that under the constraint condition of control input, the robustness of idle speed control that is being subjected to torque disturbances and noise disturbances can be greatly improved by use of the servo structure II.

Idle speed control using a describing-function approach

A new systematic method for idle speed control of uncertain automobile engines with a time delay is developed. The method is based on obtaining a describing-function model of the internal combustion engine. This is followed by designing a classical controller via an algebraic approach. The design method and the associated software are applied to a specific automobile engine, and it is shown that the results compete with the observer-based design of Bengea et al. Stability is demonstrated by successful generation of describing-function models of the final non-linear closed-loop system.

A neural network model-based observer for idle speed control of ignition in SI engine

The paper presents an algorithm of idle speed stabilization in the spark ignition automotive engine by means of spark advance control. The algorithm is based on a well-known approach of a model-based adaptive control and uses artificial neural networks. The control algorithm is based on a neural network model observer of the additional effective torque. The additional load is estimated as difference between effective torque, estimated by the neural network observer, and brake torque, estimated on the basis of a linear quadratic model. In that case the additional load is understood as the sum of the alternator brake torque (additional load form electric car equipments) and the momentary and/or permanent changes of the engine’s characteristics. On the basis of estimated values of the additional load, the required value of angular acceleration is determined to make the engine return to the specified speed. This acceleration is achieved by adjusting the spark advance. The required value of spark advance is estimated by means of a neural network model converse to that of the effective torque. The algorithm was experimentally compared with PID and adaptive algorithms in the same test bed. The tests were conducted under sudden change of external load. The proposed algorithm proved to be more effective in terms of control error.

Delay-dependent guaranteed cost control for state-delayed system with disturbance and its application to engine idle speed control

This paper proposes a delay-dependent guaranteed cost control scheme for engine idle speed control (ISC) with induction-to-torque delay and external load disturbance. An augmented linearization model of engine at idle speed operating mode was developed based on physical principle and experiment data. To provide a compromise between disturbance rejection and other performance requirements of ISC, a multi-objective cost function upper bound was given, which can help us to take into account the fuel economy and disturbance rejection performance together in ISC. Poles constraint was added to the closed-loop system to guarantee convergence rates of state. The whole optimization solution to ISC can be solved under the framework of LMI. A commercial engine model was utilized to assess the performance of the controller. Simulation results on this model show us that designed controller can achieve desired performance.

Engine idle-speed system modelling and control optimization using artificial intelligence

This paper proposes a novel modelling and optimization approach for steady state and transient performance tune-up of an engine at idle speed. In terms of modelling, Latin hypercube sampling and multiple-input and multiple-output (MIMO) least-squares support vector machines (LS-SVMs) are proposed to build an engine idle-speed model based on experimental sample data. Then, a genetic algorithm (GA) and particle swarm optimization (PSO) are applied to obtain an optimal electronic control unit setting automatically, under various user-defined constraints. All of the above techniques mentioned are artificial intelligence techniques. To illustrate the advantages of the MIMO LS-SVM, a traditional multilayer feedforward neural network (MFN) is also applied to build the engine idle-speed model. The modelling accuracies of the MIMO LS-SVM and MFN are also compared. This study shows that the predicted results using the estimated model from the LS-SVM are in good agreement with the actual test results. Moreover, both the GA and PSO optimization results show an impressive improvement on idle-speed performance in a test engine. The optimization results also indicate that PSO is more efficient than the GA in an idle-speed control optimization problem based on the LS-SVM model. As the proposed methodology is generic, it can be applied to different engine modelling and control optimization problems.

A hybrid feedback for a benchmark problem of idle speed control

AbstractThe ever increasing demands on passengers' comfort, safety, emissions and fuel consumption imposed by car manufacturers and regulations call for advanced techniques and the use of cycle‐accurate models in automotive control. In this paper, we focus on such approach to the idle speed control. It is natural to resort to hybrid methodologies, because of the rich combination of time and event‐based behaviors exhibited by a controlled engine. A hybrid benchmark problem is considered and addressed first by analyzing the equilibria of the system and then testing a simple hybrid feedback strategy. Copyright © 2009 John Wiley & Sons, Ltd.

Adaptive Kalman Filter-Based Load Torque Compensator for Improved SI Engine Idle Speed Control

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents design of an SI engine load torque estimator based on an adaptive Kalman filter. The adaptive estimator is characterized by a fast response and good noise suppression ability. The estimator is used to establish a fast load torque compensation path within a proportiona-plus-integral (PI) controller-based idle speed control system. The proposed adaptive controller has been verified by means of experiments, and compared with PI, PID and polynomial controllers. The experimental results point out to favorable performance of the adaptive controller for a wide engine operating range. </para>

Responsiveness Improvement of Idling Speed Control for Automotive Using SMC

To improve the responsiveness of engine speed control to disturbances, robust controls were investigated by simulation. The intake air control system of a gasoline engine is a typical nonlinear system, and the disturbances and parameter perturbations are generally regarded as being the unstable factors with regard to engine control. In this paper, a Mean-Value Engine Model (MVEM) with disturbances and parameter perturbations is investigated using Sliding Mode Control (SMC), which is a form of variable structure control, with a view to address instability in the idle speed control process. The simulation results confirmed that, compared with a conventional PI (Proportional-Integral) controller, the stability of the idle speed for an engine that is being subjected to disturbances, parameter variations and background noise is greatly improved by the application of SMC.

Model Based Fault Detection and Isolation in Idle Speed Control of IC Engines

A new fault diagnostics method for the idle speed control of an internal combustion (IC) engine is proposed. Two specific faults are of interest: an input fault, associated with the throttle actuator, and an output fault related to the pressure sensor. In addition, the algorithm is required to be robust to external torque loads varying from 5 to 10Nm, as well as modeling errors due performance variations of the real engine during different operating modes: cold and warm. The model based approach is characterized by residual generators and requires only two residuals and an active threshold technique to perform fault diagnosis. Simulation results show 100% fault detection during nominal temperature conditions, and 94% fault detection during initial operating stage of the engine.

Evaluation of Sliding Mode Idle-Speed Control for SI Engines

Evaluation of Sliding Mode Idle-Speed Control for SI Engines

스로틀 바디가 가솔린 엔진의 출력 및 배기배출물 특성에 미치는 영향에 관한 실험적 연구

Many researches have been carried out to reduce the emission levels and lower the fuel consumption in SI engines. Recently electronically controlled injection system is widely adapted to a passenger car to achieve these goals. Throttle body is also an important factor which influences on the emissions and engine power. In this study we redesigned a throttle body and conducted an experimental study to see the effects on engine performance and emission characteristics. We could find that idle speed control(ISC) showed stable operation characteristics as the cooling water temperature varied. And CO and HC emissions also satisfied the regulation limit.

Automotive engine idle speed control optimization using least squares support vector machine and genetic algorithm

PurposeNowadays, automotive engines are controlled by electronic control units (ECUs), and the engine idle speed performance is significantly affected by the setup of control parameters in the ECU. The engine ECU tune‐up is done empirically through tests on a dynamometer (dyno). In this way, a lot of time, fuel and human resources are consumed, while the optimal control parameters may not be obtained. The purpose of this paper is to propose a novel ECU setup optimization approach for engine idle speed control.Design/methodology/approachIn the first phase of the approach, Latin hypercube sampling (LHS) and a multi‐input/output least squares support vector machine (LS‐SVM) is proposed to build up an engine idle speed model based on dyno test data, and then a genetic algorithm (GA) is applied to obtain optimal ECU setting automatically subject to various user‐defined constraints.FindingsThe study shows that the predicted results using the estimated model from LS‐SVM are in good agreement with the actual test results. Moreover, the optimization results show a significant improvement on idle speed performance in a test engine.Practical implicationsAs the methodology is generic it can be applied to different vehicle control optimization problems.Originality/valueThe research is the first attempt to integrate a couple of paradigms (LHS, multi‐input/output LS‐SVM and GA) into a general framework for constrained multivariable optimization problems under insufficient system information. The proposed multi‐input/output LS‐SVM for modelling of multi‐input/output systems is original, because the traditional LS‐SVM modelling approach is suitable for multi‐input, but single output systems. Finally, this is the first use of the novel integrated framework for automotive engine idle‐speed control optimization.

Anti-Jerk &amp; amp; Idle Speed Control with Integrated Sub-Harmonic Vibration Compensation for Vehicles with Dual Mass Flywheels

Anti-Jerk &amp; amp; Idle Speed Control with Integrated Sub-Harmonic Vibration Compensation for Vehicles with Dual Mass Flywheels

Model-based control and learning control method for automobile idle speed control using electric throttle

Recently, it has become important to reduce the fuel consumption of automobile engines in order to reduce the amount of CO2 emission. Reduced consumption can be achieved by reducing the idle rotati...

Computerized diagnostic for the fuel injection control system

The purpose of the study is to carry out the experimental tests for the propulsion unit of the selected passenger car i.e. Skoda Felicia 1.3 MPI provided with Simos 2P system (manufactured by Siemens). The tests were carried out by means of an appropriate measuring equipment, among others AOC1K oscilloscope (digital recorder integrated with PC by means of RS232 interface) and a personal computer. The measurements of signals on the contacts of the electronic control device encompass the measuring procedures for individual signals, in accordance with the contact symbols: the camshaft position sensor, the engine speed sensor, the lambda probe, the pressure sensor, the throttle position sensor, the idle speed control actuator, the knock sensor. In some cases it is impossible to confirm the standard codes by the execution of diagnostic tests of the modern control system of ZI combustion engine, using the Simos 2P system.

Compensation of sub-harmonic vibrations during engine idle by variable fuel injection control

Today, in many passenger cars and light trucks, the conventional driveline is extended by a dual mass flywheel (DMF). The DMF reduces driveline oscillations by mechanically decoupling the transmission from the periodic combustion events that excite the engine crankshaft. Existing engine control systems are designed for conventional single mass flywheel (SMF) systems. In the future, to facilitate the optimal control of engines equipped with advanced DMF systems, such conventional control systems may require adaptation, modification or even replacement. The basic task of idle speed control systems is to maintain a defined setpoint of rotational engine speed independent from engine operating conditions (e.g. load disturbances). Due to the torque reactions of the DMF, control systems designed for engines with SMF can be disturbed, leading to unstable engine idle (e.g. sub-harmonic vibrations, oscillations following load rejection, etc.) In this approach, an optimised solution for idle speed control regarding conventional combustion engines equipped with DMF is introduced. The enhanced control system is based on conventional PID-control strategies with improved fuel injection scheduling. Using incremental (i.e. tooth-to-tooth) engine speed, critical dead times, which can lead to limit cycles in non-linear closed-loop control circuits, are minimised. Limit cycles, which are distinguishable as sub-harmonic vibrations at the same frequency, are effectively reduced by improving load rejection at idle. The implementation of these solutions in current engine management systems requires no additional sensors or other hardware.

Unified MPC strategy for idle-speed control, vehicle start-up and gearing applied to an Automated Manual Transmission

A real-time Model Predictive Control (MPC) is proposed for controlling the behavior of an Automated Manual Transmission (AMT). The underlying formulation shows a unified approach that handles different modes: idle-speed control, vehicle start-up, gearing up and down. Sub-optimal solutions are computed on line using an adaptive reduced dimensional parametrization that is directly linked to the accelerator pedal position. Transmission stability constraints are explicitly handled as well as saturations on the control inputs. The proposed control is tested both in simulation and on line in a city car demonstrator equipped with a natural gas engine.

Modeling, Identification, Design, and Implementation of Nonlinear Automotive Idle Speed Control Systems—An Overview

Automotive idle speed control (ISC) is one of the most challenging aspects in engine control fields. Essentially it is a highly nonlinear, time-varying, complicated, and uncertain dynamic control problem. As the typical automotive transient operation, the quality of the ISC has a significant impact on fuel economy, emission levels (HC, CO, and NOx), combustion stability, transient response, and noise, vibration, and harshness characteristics. This paper presents a thorough review of various dynamic control technologies which have been successfully applied to ISC systems. In particular, practical implementations on a variety of different engine types are provided, which cover broad areas of control, including classical control, modern control, and intelligent control. Over 90 selected papers published during the last two decades are reviewed and then summarized from a control point of view. These control approaches can be generalized to the control of other automotive, electrical, mechanical, and aeronautical systems.