EASILY VERIFIABLE CONTROLLER DESIGN WITH APPLICATION TO AUTOMOTIVE POWERTRAINS

Bridging the gap between designed and implemented model-based controllers is a major challenge in the design cycle of industrial controllers. This gap is mainly created due to (i) digital implementation of controller software that introduces sampling and quantization imprecisions via analog-to-digital conversion (ADC), and (ii) uncertainties in the modeled plant’s dynamics, which directly propagate through the controller structure. The failure to identify and handle these implementation and model uncertainties results in undesirable controller performance and costly iterative loops for completing the controller verification and validation (V&V) process. This PhD dissertation develops a novel theoretical framework to design controllers that are robust to implementation imprecision and uncertainties within the models. The proposed control framework is generic and applicable to a wide range of nonlinear control systems. The final outcome from this study is an uncertainty/imprecisions adaptive, easily verifiable, and robust control theory framework that minimizes V&V iterations in the design of complex nonlinear control systems. The concept of sliding mode controls (SMC) is used in this study as the baseline to construct an easily verifiable model-based controller design framework. SMC is a robust and computationally efficient controller design technique for highly nonlinear systems, in the presence of model and external uncertainties. The SMC structure allows for further modification to improve the controller robustness against implementation imprecisions, and compensate for the uncertainties within the plant model. First, the conventional continuous-time SMC design is improved by: (i) developing a reduced-order controller based on a novel model order reduction technique. The reduced order SMC shows better performance, since it uses a balanced realization form of the plant model and reduces the destructive internal interaction among different states of the system. (ii) developing an uncertainty-adaptive SMC with improved robustness against implementation imprecisions. Second, the continuous-time SMC design is converted to a discrete-time SMC (DSMC). The baseline first order DSMC structure is improved by: (i) inclusion of the ADC imprecisions knowledge via a generic sampling and quantization uncertainty prediction mechanism which enables higher robustness against implementation imprecisions, (ii) deriving the adaptation laws via a Lyapunov stability analysis to overcome uncertainties within the plant model, and (iii) developing a second order adaptive DSMC with predicted ADC imprecisions, which provides faster and more robust performance under modeling and implementation imprecisions, in comparison with the first order DSMC. The developed control theories from this PhD dissertation have been evaluated in real-time for two automotive powertrain case studies, including highly nonlinear combustion engine, and linear DC motor control problems. Moreover, the DSMC with predicted ADC imprecisions is experimentally tested and verified on an electronic air throttle body testbed for model-based position tracking purpose

Artificial Tune of Fuel Ratio: Design a Novel SISO Fuzzy Backstepping Adaptive Variable Structure Control

This paper examines single input single output (SISO) chattering free variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. VSC methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. The main goal is to guarantee acceptable fuel ratio result and adjust. The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. The input represents the function between variable structure function, error and the rate of error. The outputs represent fuel ratio, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBSAVSC) is validated through comparison with VSC and proposed method. Simulation results signify good performance of trajectory in presence of uncertainty torque load. DOI:http://dx.doi.org/10.11591/ijece.v3i2.209

Real time implementation of socially acceptable collision avoidance of a low speed autonomous shuttle using the elastic band method

This paper presents the real time implementation of socially acceptable collision avoidance using the elastic band method for low speed autonomous shuttles operating in high pedestrian density environments. The modeling and validation of the research autonomous vehicle used in the experimental implementation is presented first, followed by the details of the Hardware-In-the-Loop connected and autonomous vehicle simulator used. The socially acceptable collision avoidance algorithm is formulated using the elastic band method as an online, local path modification algorithm. Parameter space based robust feedback plus feedforward steering controller design is used. Model-in-the-loop, Hardware-In-the-Loop and road testing in a proving ground are used to demonstrate the effectiveness of the real time implementation of the elastic band based socially acceptable collision avoidance method of this paper

Automotive Powertrain Control — A Survey

This paper surveys recent and historical publications on automotive powertrain control. Control-oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72023/1/j.1934-6093.2006.tb00275.x.pd

Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems

The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations. As more mechanical functions are being replaced by electric or electronic devices, the IC engine systems are becoming more complex in structure. Sophisticated control strategies are called in to help the engine systems meet the drivability demands and to comply with the emission regulations. Different model-based or data-driven algorithms have been applied to the optimization and control of IC engine systems. For the conventional model-based algorithms, the accuracy of the applied system models has a crucial impact on the quality of the feedback system performance. With computable analytic solutions and a good estimation of the real physical processes, the model-based control embedded systems are able to achieve good transient performances. However, the analytic solutions of some nonlinear models are difficult to obtain. Even if the solutions are available, because of the presence of unavoidable modeling uncertainties, the model-based controllers are designed conservatively

Adaptive torque-feedback based engine control

The aim of this study was to develop a self-tuning or adaptive SI engine controller using torque feedback as the main control variable, based on direct/indirect measurement and estimation techniques. The indirect methods include in-cylinder pressure measurement, ion current measurement, and crankshaft rotational frequency variation. It is proposed that torque feedback would not only allow the operating set-points to be monitored and achieved under wider conditions (including the extremes of humidity and throttle transients), but to actively select and optimise the set-points on the basis of both performance and fuel economy. A further application could allow the use of multiple fuel types and/or combustion enhancing methods to best effect. An existing experimental facility which comprised a Jaguar AJ-V8 SI engine coupled to a Heenan-Froude Dynamatic GVAL (Mk 1) dynamometer was adopted for this work, in order to provide a flexible distributed engine test system comprising a combined user interface and cylinder pressure monitoring system, a functional dynamometer controller, and a modular engine controller which is close coupled to an embedded PC has been created. The considerable challenges involved in creating this system have meant that the core research objectives of this project have not been met. Nevertheless, an open-architecture software and hardware engine controller and independent throttle controller have been developed, to the point of testing. For the purposes of optimum ignition timing validation and combustion knock detection, an optical cylinder pressure measurement system with crank angle synchronous sampling has been developed. The departure from the project’s initial aims have also highlighted several important aspects of eddy-current dynamometer control, whose closed-loop behaviour was modelled in Simulink to study its control and dynamic response. The design of the dynamometer real-time controller was successfully implemented and evaluated in a more contemporary context using an embedded digital controller.EThOS - Electronic Theses Online ServiceSchool of Mechanical & Systems EngineeringNewcastle UniversityGBUnited Kingdo

Transitional controller design for adaptive cruise control systems

Traffic congestion is an important reason for driver frustration which in turn is the main cause of human errors and accidents. Statistics reports have shown that over 90% of accidents are caused by human errors. Therefore, it is vital to improve vehicle controls to ensure adequate safety measures in order to decrease the number of accidents or to reduce the impact of accidents. An application of mathematical control techniques to the longitudinal dynamics of a vehicle equipped with an adaptive cruise control (ACC) system is presented. This study is carried out for the detailed understanding of a complex ACC vehicle model under critical transitional manoeuvres (TMs) in order to establish safe inter-vehicle distance with zero range-rate (relative velocity) behind a preceding vehicle. TMs are performed under the influence of internal complexities from vehicle dynamics and within constrained operation boundaries. The constrained boundaries refer to the control input, states, and collision avoidance constraints. The ACC vehicle is based on a nonlinear longitudinal model that includes vehicle inertial and powertrain dynamics. The overall system modelling includes: complex vehicle models, engine maps construction, first-order vehicle modelling, controllers modelling (upper-level and lower-level controllers for ACC vehicles). The upper-level controller computes the desired acceleration commands for the lower-lever controller which then provides the throttle/brake commands for the complex vehicle model. An important aspect of this study is to compare four control strategies: proportional-integral-derivative; sliding mode; constant-time-gap; and, model predictive control for the upper-level controller analysis using a first-order ACC vehicle model. The first-order model represents the lags in the vehicle actuators and sensor signal processing and it does not consider the dynamic effects of the vehicle’s sub-models. Furthermore, parameter analyses on the complex ACC vehicle for controller and vehicle parameters have been conducted. The comparison analysis of the four control strategies shows that model predictive control (MPC) is the most appropriate control strategy for upper-level control because it solves the optimal control problem on-line, rather than off-line, for the current states of the system using the prediction model, at the same time being able to take into account operation constraints. The analysis shows that the complex ACC vehicle can successfully execute TMs, tracking closely the desired acceleration and obeying the constraints, whereas the constraints are only applied in the MPC controller formulation. It is found that a higher length of the prediction horizon should be used for a closed acceleration tracking. The effect of engine and transmission dynamics on the MPC controller and ACC vehicle performance during the gear shifting is studied. A sensitivity analysis for MPC controller and vehicle parameters indicates that a length of the control horizon that is too high can seriously disturb the vehicle behaviour, and this disturbance can be only removed if a higher value of control input cost weighting is used. Furthermore, the analysis indicates that a mass within the range of 1400-2000 kg is suitable for the considered ACC vehicle. It is recommended that a variable headway time should be used for the spacing control between the two vehicles. It is found that the vehicle response is highly sensitive to the control input cost weighting; a lower value (less than one) can lead to a highly unstable vehicle response. It is recommended that the lower-level controller must take into account the road gradient information because the complex ACC vehicle is unable to achieve the control objectives while following on a slope. Based on the results, it is concluded that a first-order ACC vehicle model can be used for the controller design, but it is not sufficient to capture the complex vehicle dynamic response. Therefore, a complex vehicle model should be of use for the detailed ACC vehicle analysis. In this research study the first-order ACC vehicle model is used for the complex vehicle validation, whereas the complex ACC vehicle model can be used for the experimental validation in future work

State Estimation and Control of Active Systems for High Performance Vehicles

In recent days, mechatronic systems are getting integrated in vehicles ever more. While stability and safety systems such as ABS, ESP have pioneered the introduction of such systems in the modern day car, the lowered cost and increased computational power of electronics along with electrification of the various components has fuelled an increase in this trend. The availability of chassis control systems onboard vehicles has been widely studied and exploited for augmenting vehicle stability. At the same time, for the context of high performance and luxury vehicles, chassis control systems offer a vast and untapped potential to improve vehicle handling and the driveability experience. As performance objectives have not been studied very well in the literature, this thesis deals with the problem of control system design for various active chassis control systems with performance as the main objective. A precursor to the control system design is having complete knowledge of the vehicle states, including those such as the vehicle sideslip angle and the vehicle mass, that cannot be measured directly. The first half of the thesis is dedicated to the development of algorithms for the estimation of these variables in a robust manner. While several estimation methods do exist in the literature, there is still some scope of research in terms of the development of estimation algorithms that have been validated on a test track with extensive experimental testing without using research grade sensors. The advantage of the presented algorithms is that they work only with CAN-BUS data coming from the standard vehicle ESP sensor cluster. The algorithms are tested rigorously under all possible conditions to guarantee robustness. The second half of the thesis deals with the design of the control objectives and controllers for the control of an active rear wheel steering system for a high performance supercar and a torque vectoring algorithm for an electric racing vehicle. With the use of an active rear wheel steering, the driver’s confidence in the vehicle improves due a reduction in the lag between the lateral acceleration and the yaw rate, which allows drivers to push the vehicle harder on a racetrack without losing confidence in it. The torque vectoring algorithm controls the motor torques to improve the tire utilisation and increases the net lateral force, which allows professional drivers to set faster lap times

Adaptive control of plants with input saturation: an approach for performance improvement

In this work, a new method for adaptive control of plants with input saturation is presented. The new anti-windup scheme can be shown to result in bounded closed-loop states under certain conditions on the plant and the initial closed-loop states. As an improvement in comparison to existing methods in adaptive control, a new degree of freedom is introduced in the control scheme. It allows to improve the closed-loop response when actually encountering input saturation without changing the closed-loop performance for unconstrained inputs.Diese Arbeit präsentiert eine neue Methode für die adaptive Regelung von Strecken mit Stellgrößenbegrenzung. Für das neue anti-windup Verfahren wird gezeigt, dass die Zustände des Regelkreises begrenzt bleiben, wenn dessen initiale Werte und die Regelstrecke bestimmte Bedingungen erfüllen. Eine Verbesserung im Vergleich zu existierenden Methoden wird durch die Einführung eines zusätzlichen Freiheitsgrades erzielt. Dieser erlaubt die Verbesserung der Regelgüte des geschlossenen Regelkreises, wenn das Eingangssignal sich in der Limitierung befindet, ohne diese sonst zu verändern