샤시 제어를 위한 동적 목표 요레이트 설계

학위논문 (석사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 이경수.Abstract Dynamic Target Yaw-rate Design for Chassis Control Kwanwoo Park School of Mechanical and Aerospace Engineering The Graduate School Seoul National University This paper presents a dynamic target yaw-rate design method for chassis control system. The target yaw-rate is essential for the supervisor of the Integrated Chassis Control(ICC) algorithm. The supervisory controller monitors the vehicle status and determines desired vehicle motions such as a target yaw-rate. The target design is important because the inputs such as lateral force, yaw moment are calculated according to this target motion in the upper and lower level controller. Conventional target design is parameter optimization for a specific scenario and road condition. However, this has the disadvantage of lacking interchangeability between different scenarios. In this paper, research has been conducted to make the target yaw-rate design universal. The proposed design method consists of two parts: A bicycle model, which is considered transient handling characteristic, and Relaxation Length Tire (RLT) model which is the dynamic tire model. First, the existing bicycle cornering kinematics that assumes the steady state is reformulated as a model considering the yaw acceleration, a transient characteristic. Second, the target yaw-rate considering the RLT model serves to compensate the phase delay. The proposed method can contributes to securing the performance and lateral stability of the Integrated Chassis Control(ICC) system by increasing the responsiveness of the model to the level of the actual vehicle. After investigating the suitability of the vehicle motion simulation, it is also investigated the influence of the control input required by using the direct yaw moment control when applying it as the supervisor of the chassis control algorithm. The proposed method has been investigated under several standard maneuvers via simulation with CarSim vehicle dynamics software and Matlab/Simulink and vehicle test data. The results show the proposed target yaw-rate which is incorporating transient handling characteristics well represents natural vehicle response such as phase delay and agility from mild handling maneuver to the limit handling maneuver. It has also been confirmed that it can alleviate the sense of difference that the driver felt from the existing over-control. Keywords: Chassis control, Target yaw-rate design, Vehicle stability control, Lateral vehicle dynamics, Transient handling characteristics Student Number: 2015-22713Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Purpose of Research 2 Chapter 2 Analysis of Vehicle Dynamics 2.1 Lateral Vehicle Dynamics and Kinematics 4 2.2 Vehicle Stability Control 8 Chapter 3 Supervisor of Chassis Control System 17 3.1 Conventional Target Yaw-rate Design 19 3.2 Modified Target Yaw-rate Design 21 3.2.1 Transient handling characteristics 21 3.2.2 Dynamic Tire Model 23 Chapter 4 Comparison / Validation 28 4.1 Validation of Target Yaw-rate Design 31 4.1.1 Scenario 1: Constant Circular Turning with Acceleration 31 4.1.2 Scenario 2: Mild Handling Maneuver 32 4.1.3 Scenario 3: Limit Handling Maneuver 36 4.2 Performance of Target Yaw-rate Design 38 Chapter 5 Conclusion and Future Work 40 Bibliography 42 국문초록 45Maste

Simulation of Electric Vehicles Combining Structural and Functional Approaches

In this paper the construction of a model that represents the behavior of an Electric Vehicle is described. Both the mechanical and the electric traction systems are represented using Multi-Bond Graph structural approach suited to model large scale physical systems. Then the model of the controllers, represented with a functional approach, is included giving rise to an integrated model which exploits the advantages of both approaches. Simulation and experimental results are aimed to illustrate the electromechanical interaction and to validate the proposal.Fil: Silva, Luis Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingeniería. Grupo de Electronica Aplicada; ArgentinaFil: Magallán, Guillermo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingeniería. Grupo de Electronica Aplicada; ArgentinaFil: de la Barrera, Pablo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingeniería. Grupo de Electronica Aplicada; ArgentinaFil: de Angelo, Cristian Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingeniería. Grupo de Electronica Aplicada; ArgentinaFil: Garcia, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingeniería. Grupo de Electronica Aplicada; Argentin

Integrated Chassis Control of Active Front Steering and Yaw Stability Control Based on Improved Inverse Nyquist Array Method

An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method

Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation

극한 주행 성능 향상을 위한 타이어 슬립 정보 기반 통합 샤시제어 알고리즘

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2016. 8. 이경수.This paper presents a tire slip based integrated chassis control (ICC) algorithm of four-wheel drive(4WD)/ electronic stability control(ESC)/electronic controlled suspension(ECS) for enhanced limit handling. The principal objective of the vehicle dynamic control algorithm for limit handling is to enable agile, steady maneuver at the limits and expand vehicle control capability to maximum. In order to achieve this objective, the ICC consists of three layers - a supervisor, an upper level controller, and a lower level controller. The supervisor determines desired vehicle motions based on driver commands to the vehicle. The upper level controller calculated virtual control inputs based on desired vehicle motion. In the lower level controller, the virtual control inputs are optimally coordinated to each chassis module based on tire combined slip for enhanced limit handling. The performance of ICC has been investigated via closed loop simulation and vehicle experiment. To investigate the ICC algorithm at the limits via closed loop simulation, the lateral driver model, which mimics professional drivers, for limit handling has been developed and utilized. In the developed driver model, body side slip angle incorporates into path tracking error in contrast to common path tracking algorithms. It has been shown that the proposed ICC algorithm effectively keeps stability and maneuverability of the vehicle at the limits.Chapter 1 Introduction 1 1.1 Study Background 1 1.2 Purpose of Research 3 Chapter 2 Vehicle Control System 5 2.1 Vehicle Chassis System 5 Chapter 3 Lateral Driver Model 8 3.1 Overall Algorithm 8 3.2 Comparison and Validation 23 Chapter 4 Development of Integrated Chassis Control Algorithm of ESC and 4WD for Enhanced Limit Handling 32 4.1 Supervisor 32 4.2 Uppel Level Controller 34 4.3 Lower Level Controller: Optimal Coordination 37 4.4 Simulation Results 47 Chapter 5 Development of Integrated Chassis Control Algorithm of ESC, 4WD, ECS and ARS for Enhanced Limit Handling 58 5.1 Supervisor 58 5.2 Upper Level Controller 59 5.3 ECS/ARS Control Allocation 59 5.4 Comparison and validation 64 Chapter 6 Vehicle Tests of 4WD/ESC/ECS Algorithm 71 6.1 Experimental Results 72 Chapter 7 Conclusion & Future Works 73 Bibliography 75 국문 초록 78Maste

Systematization of integrated motion control of ground vehicles

This paper gives an extended analysis of automotive control systems as components of the integrated motion control (IMC). The cooperation of various chassis and powertrain systems is discussed from a viewpoint of improvement of vehicle performance in relation to longitudinal, lateral, and vertical motion dynamics. The classification of IMC systems is proposed. Particular attention is placed on the architecture and methods of subsystems integration

직렬형 하이브리드 기반 6륜 인휠 차량의 최적 주행성, 안정성 및 에너지 효율을 위한 주행제어 알고리즘 개발

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 자동차공학전공, 2012. 8. 이경수.본 논문은 직렬형 하이브리드 기반 6륜 인휠차량의 최적 주행성, 안정성 및 에너지 효율을 위한 주행제어 알고리즘 개발에 대하여 서술하였다. 대상 차량은 구동, 제동 및 조향이 독립적으로 가능한 시스템으로 구성되어 있다. 통합 주행제어 알고리즘은 6WD/6WS 차량의 최적 안정성, 주행성 및 에너지 효율을 위해 개발되었습니다. 제안된 알고리즘은 목표 동역학, 상위 제어, 하위 제어, 동력관리 계층을 포함하여 크게 4부분으로 구성되어 있습니다. 목표 동역학 계층은 운전자의 조향, 구동 및 제동 입력을 통해 각 휠의 조향각과 목표 속도 및 제동량을 결정합니다. 안정성 판단/제어, 요 모멘트 제어 및 속도 제어는 상위 제어기에 포함되어 있다. 안정성 판단/제어는 차량의 안정성을 판단하여 횡안정성 및 전복 안정성을 확보하기 위하여 G-vectoring과 요 모멘트 제어를 실시한다. 요 모멘트 제어는 요 안정성을 확보하기 위해 목표 요 속도를 만족시키는 목표 요 모멘트를 결정한다. G-vectoring 제어는 과도한 횡 가속도를 줄이기 위하여 종방향 가속도를 차량에 작용하게 하여 전복 안정성을 확보 하도록 설계하였다. 속도 제어는 운전자의 의도를 만족하기 위하여 슬라이딩 제어 기법을 기반으로 설계되었다. 하위 제어기는 각 휠의 슬립 상황, 인휠 모터의 토크 제한등을 고려하여 각 휠에 분배된다. 이를 위하여 Control Allocation 기법이 사용되었으며, 실시간 구현을 위하여 4가지 해석 기법을 개발하고 적용하여 적합한 알고리즘을 적용하였다. 동력관리 제어는 차량 구동에 있어서 연료소모량을 최소로 하기 위한 전략을 기반으로 설계되었다. 등가 연료 소모량 최소 전략 (ECMS)이 사용되어 최적의 연료 효율을 확보하였다. 제어기 성능 검증을 위하여 컴퓨터 시뮬레이션을 수행하였다. 시뮬레이션 결과를 통해 일반 차량의 성능과 비교하여, 크게 향상된 안정성, 주행성 및 에너지 효율을 확인 하였다.This paper describes an integrated driving control algorithm for optimized maneuverability and stability of a six-wheeled driving/brake and six-wheeled steering (6WD/6WS) electric combat vehicle which is equipped with drive/brake-by-wire and steer-by-wire modules. This integrated driving control algorithm is developed to obtain optimized stability, maneuverability and energy efficiency of a 6WD/6WS vehicle. The proposed control algorithm consists of four parts: desired dynamics, upper level control, lower level control and power management algorithm. The desired dynamics determines the steering angle of each wheel and the desired acceleration according to drivers steering, throttle, and braking inputs. Stability decision/control, yaw moment control, and speed control algorithms are included in the upper level control layer in order to track the desired dynamics and guarantee yaw and roll stability. The lower level control layer which is based on a control allocation method computes actuator commands, such as independent driving and regenerative braking torques. In the upper level control layer, the stability decision algorithm defines stability regions on a g-g diagram and calculates the desired longitudinal acceleration based on a G-vectoring control method and the desired yaw rate for lateral and yaw stability, and rollover prevention. The G-vectoring control algorithm determines the longitudinal acceleration required to keep the vehicle stable. The speed control calculates the desired longitudinal net force, and the desired net yaw moment is determined to track the desired yaw rate. Control allocation method is used to design the lower level control layer. Limitations related to the physical maximum output torque and prevention of excessive wheel slip are defined as control input constraints of control allocation, which takes friction circle information into account. For real-time implementation, four candidate methods have been designed and developed to solve the control allocation problem. Feasible method has been adopted, taking execution time into account in order to obtain optimized solutions. In the power management layer, from the determined input torque, the required power can be calculated. The required engine/generator and battery power are determined to minimize energy consumption. Fuel consumption minimization strategy (ECMS) is useful for on-line optimization and adopted to implement real-time applications. Computer simulations have been conducted to evaluate the proposed integrated driving control algorithm. It has been shown from simulation results that, compared to conventional drive systems, significantly improved vehicle maneuverability and stability can be obtained by the proposed integrated control algorithm.Abstract i List of Tables viii List of Figures ix Nomenclature xiii Chapter 1. Introduction 1 1.1 Background and Motivation 1 1.2 Previous Researches 3 1.2.1 Lateral Stability Control System 3 1.2.2 Torque Vectoring Control System 5 1.2.3 G-Vectoring Control System 7 1.2.4 Control Allocation 8 1.2.5 Power Management Control System 9 1.3 Thesis Objectives 11 1.4 Thesis Outline 13 Chapter 2. Control System Modeling 15 2.1 Control System Overview 15 2.2 Control System Architecture 18 2.3 Vehicle Dynamic, Actuators and Power System Model 20 2.3.1 Vehicle dynamic model 20 Body dynamics 21 Tire dynamics 22 2.3.2 Motor Dynamic model 24 2.3.3 Power System Model 25 2.3.4 Plannar Model for Control System Design 28 Stability analysis of the proposed 6WD/6WS platform 32 2.3.5 Bicycle model for Direct Yaw Moment Control Design 36 Chapter 3. Integrated Driving Control Algorithm 37 3.1 Desired Dynamics Layer 38 3.1.1 Desired steering angle determination 38 3.1.2 Desired velocity determination 40 3.2 Upper Level Control Layer 44 3.2.1 Stability decision algorithm 44 3.2.2 G-vectoring control algorithm 49 Accessibility of the G-vectoring control algorithm 50 Controllability of the G-vectoring control algorithm 53 Design of G-vectoring control algorithm 55 3.2.3 Yaw moment control algorithm 59 Performance verification based on frequency analysis 64 3.2.4 Speed control algorithm 70 Velocity tracking algorithm 71 Acceleration tracking algorithm 72 Switching algorithm 72 3.2.5 Stability analysis of the proposed control system 73 3.3 Lower Level Control Layer 79 3.3.1 Control Allocation Formulation 79 Cost function and constraints definition for control allocation problem formulation 81 Actuator Limitation Algorithm 91 Slip Limitation Algorithm 93 3.3.2 Fixed-point (FXP) control allocation method 97 3.3.3 Cascaded Generalized pseudo-inverse (CGI) method 99 3.3.4 Interior point (IP) method 101 3.3.5 Weighted least square method (WLS) 107 3.3.6 Implementation of control allocation 112 Unsaturated condition of control inputs 113 Saturated condition of control inputs 116 3.4 Power Management Layer 121 3.4.1 Equivalent fuel consumption minimization stratery(ECMS) 121 3.4.2 Design of engine/generator control algorithm 130 Chapter 4. Estimator Design 132 4.1 Longitudinal tire force estimation 133 4.2 Friction circle estimation 136 Chapter 5. Simulation Results 143 5.1 Turning Performance Verification – Open loop 151 5.2 Turning Performance Verification with Braking 156 5.3 Turning Performance Verification – Closed- loop 160 5.4 Lateral Stability Verification 162 5.5 Rollover Stability Verification 170 5.6 Driving Performance Verification for Gradient Road 173 5.7 Performance Verification of Energy Efficiency 175 5.8 Integrated Performance Verification using Test Track 186 5.9 Integrated Performance Verification using Test Track (DLC included) 195 Bibliography 202 국문초록 208Docto

AN INTEGRATED SYSTEMS ENGINEERING METHODOLOGY FOR DESIGN OF VEHICLE HANDLING DYNAMICS

The primary objective of this research is to develop an integrated system engineering methodology for the conceptual design of vehicle handling dynamics early on in the product development process. A systems engineering-based simulation framework is developed that connects subjective, customer-relevant handling expectations and manufacturers\u27 brand attributes to higher-level objective vehicle engineering targets and consequently breaks these targets down into subsystem-level requirements and component-level design specifications. Such an integrated systems engineering approach will guide the engineering development process and provide insight into the compromises involved in the vehicle-handling layout, ultimately saving product development time and costs and helping to achieve a higher level of product maturity early on in the design phase. The proposed simulation-based design methodology for the conceptual design of vehicle handling characteristics is implemented using decomposition-based Analytical Target Cascading (ATC) techniques and evolutionary, multi-objective optimization algorithms coupled within the systems engineering framework. The framework is utilized in a two-layer optimization schedule. The first layer is used to derive subsystem-level requirements from overall vehicle-level targets. These subsystem-level requirements are passed on as targets to the second layer of optimization, and the second layer derives component-level specifications from the subsystem-level requirements obtained from the first step. The second layer optimization utilizes component-level design variables and analysis models to minimize the difference between the targets transferred from the vehicle level and responses generated from the component-level analysis. An iterative loop is set up with an objective to minimize the target/response consistency constraints (i.e., the targets at the vehicle level are constantly rebalanced to achieve a consistent and feasible solution). Genetic Algorithms (GAs) are used at each layer of the framework. This work has contributed towards development of a unique approach to integrate market research into the vehicle handling design process. The framework developed for this dissertation uses Original Equipment Manufacturer\u27s (OEM\u27s) brand essence information derived from market research for the derivation and balancing of vehicle-level targets, and guides the chassis design direction using relative brand attribute weights. Other contributions from this research include development of empirical relationships between key customer-relevant vehicle handling attributes selected from market survey and the various scenarios and objective metrics of vehicle handling, development of a goal programming based approach for the selection of the best solution from a set of Pareto-optimal solutions obtained from genetic algorithms and development of Vehicle Handling Bandwidth Diagrams

Research on Stability Control Based on the Wheel Speed Difference for the AT Vehicles

This paper utilizes a linear two-degree-of-freedom vehicle model to calculate the nominal value of the vehicle’s nondrive-wheel speed difference and investigates methods of estimating the yaw acceleration and sideslip angular speed. A vehicular dynamic stability control system utilizing this nondrive-wheel speed difference is then developed, which can effectively improve a vehicle’s dynamic stability at a very low cost. Vehicle cornering processes on roads of different frictions and with different vehicle speeds are explored via simulation, with speed control being applied when vehicle speed is high enough to make the vehicle unstable. Driving simulator tests of vehicle cornering capacity on roads of different friction coefficients are also conducted

Synthesis and Analysis of an Active Independent Front Steering (AIFS) System

Technological developments in road vehicles over the last two decades have received considerable attention towards pushing the safe performance limits to their ultimate levels. Towards this goal, Active Front Steering (AFS) and Direct Yaw-moment Control (DYC) systems have been widely investigated. AFS systems introduce corrective steering angles to the conventional system in order to realize a target handling response for a given speed and steering input. An AFS system, however, may yield limited performance under severe steering maneuvers involving substantial lateral load shift and saturation of the inside tire-road adhesion. The adhesion available at the outer tire, on the other hand, would remain under-utilized. This dissertation explores effectiveness of an Active Independent Front Steering (AIFS) system that could introduce a corrective measure at each wheel in an independent manner. The effectiveness of the AIFS system was investigated firstly through simulation of a yaw-plane model of a passenger car. The preliminary simulation results with AIFS system revealed superior potential compared to the AFS particularly in the presence of greater lateral load shift during a high-g maneuver. The proposed concept was thus expected to be far more beneficial for enhancement of handling properties of heavy vehicles, which invariably undergo large lateral load shift due to their high center of mass and roll motion. A nonlinear yaw-plane model of a two-axle single-unit truck, fully and partially loaded with solid and liquid cargo, with limited roll degree-of-freedom (DOF) was thus developed to study the performance potentials of AIFS under a range of steering maneuvers. A simple PI controller was synthesized to track the reference yaw rate response of a neutral steer vehicle. The steering corrections, however, were limited such that none of the tires approach saturation. For this purpose, a tire saturation zone was identified considering the normalized cornering stiffness property of the tire. The controller strategy was formulated so as to limit the work-load magnitude at a pre-determined level to ensure sufficient tire-road adhesion reserve to meet the braking demand, when exists. Simulation results were obtained for a truck model integrating AFS and AIFS systems subjected to a range of steering maneuvers, namely: a J-turn maneuver on uniform as well as split-μ road conditions, and path change and obstacle avoidance maneuvers. The simulation results showed that both AFS and AIFS can effectively track the target yaw rate of the vehicle, while the AIFS helped limit saturation of the inside tire and permitted maximum utilization of the available tire-road adhesion of the outside tire. The results thus suggested that the performance of an AIFS system would be promising under severe maneuvers involving simultaneous braking and steering, since it permitted a desired adhesion reserve at each wheel to meet a braking demand during the steering maneuver. Accordingly, the vehicle model was extended to study the dynamic braking characteristics under braking-in-turn maneuvers. The simulation results revealed the most meritorious feature of the AIFS in enhancing the braking characteristics of the vehicle and reducing the stopping time during such maneuvers. The robustness of the proposed control synthesis was subsequently studied with respect to parameter variations and external disturbance. This investigation also explores designs of fail-safe independently controllable front wheels steering system for implementation of the AIFS concept