Development and Experimental Evaluation of a Slip Angle Estimator for Vehicle Stability Control
01 Jan 2009-IEEE Transactions on Control Systems and Technology (Institute of Electrical and Electronics Engineers Inc.)-Vol. 17, Iss: 1, pp 78-88
TL;DR: A real-time algorithm for estimation of slip angle using inexpensive sensors normally available for yaw stability control applications that compensates for the presence of road bank angle and variations in tire-road characteristics is developed.
Abstract: Real-time knowledge of the slip angle in a vehicle is useful in many active vehicle safety applications, including yaw stability control, rollover prevention, and lane departure avoidance. Sensors to measure slip angle, including two-antenna GPS systems and optical sensors, are too expensive for ordinary automotive applications. This paper develops a real-time algorithm for estimation of slip angle using inexpensive sensors normally available for yaw stability control applications. The algorithm utilizes a combination of model-based estimation and kinematics-based estimation. Compared with previously published results on slip angle estimation, this present paper compensates for the presence of road bank angle and variations in tire-road characteristics. The developed algorithm is evaluated through experimental tests on a Volvo XC90 sport utility vehicle. Detailed experimental results show that the developed system can reliably estimate slip angle for a variety of test maneuvers.
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TL;DR: An H∞-based delay-tolerant linear quadratic regulator (LQR) control method is proposed and a generalized proportional-integral control approach is adopted to achieve a good steady-state response.
Abstract: This paper deals with the lateral motion control of four-wheel-independent-drive electric vehicles (4WID-EVs) subject to onboard network-induced time delays. It is well known that the in-vehicle network and x-by-wire technologies have considerable advantages over the traditional point-to-point communication. However, on the other hand, these technologies would also induce the probability of time-varying delays, which would degrade control performance or even deteriorate the system. To enjoy the advantages and deal with in-vehicle network delays, an H∞-based delay-tolerant linear quadratic regulator (LQR) control method is proposed in this paper. The problem is described in the form of an augmented discrete-time model with uncertain elements determined by the delays. Delay uncertainties are expressed in the form of a polytope using Taylor series expansion. To achieve a good steady-state response, a generalized proportional-integral control approach is adopted. The feedback gains can be obtained by solving a sequence of linear matrix inequalities (LMIs). Cosimulations with Simulink and CarSim demonstrate the effectiveness of the proposed controller. Comparison with a conventional LQR controller is also carried out to illustrate the strength of explicitly dealing with in-vehicle network delays.
292 citations
TL;DR: A control architecture that has the potential of improving yaw stability control by achieving faster convergence and reduced impact on the longitudinal dynamics is investigated and is capable of real-time execution in automotive-grade electronic control units.
Abstract: Vehicle active safety receives ever increasing attention in the attempt to achieve zero accidents on the road. In this paper, we investigate a control architecture that has the potential of improving yaw stability control by achieving faster convergence and reduced impact on the longitudinal dynamics. We consider a system where active front steering and differential braking are available and propose a model predictive control (MPC) strategy to coordinate the actuators. We formulate the vehicle dynamics with respect to the tire slip angles and use a piecewise affine (PWA) approximation of the tire force characteristics. The resulting PWA system is used as prediction model in a hybrid MPC strategy. After assessing the benefits of the proposed approach, we synthesize the controller by using a switched MPC strategy, where the tire conditions (linear/saturated) are assumed not to change during the prediction horizon. The assessment of the controller computational load and memory requirements indicates that it is capable of real-time execution in automotive-grade electronic control units. Experimental tests in different maneuvers executed on low-friction surfaces demonstrate the high performance of the controller.
281 citations
TL;DR: Using the estimated sideslip angle and tire cornering stiffness, the vehicle stability control system, making best use of the advantages of IMW-EVs with a steer-by-wire system, is proposed.
Abstract: This paper presents a method for using lateral tire force sensors to estimate vehicle sideslip angle and to improve vehicle stability of in-wheel-motor-driven electric vehicles (IWM-EVs) Considering that the vehicle motion is governed by tire forces, lateral tire force measurements give practical benefits in estimation and motion control To estimate the vehicle sideslip angle, a state observer derived from the extended-Kalman-filtering (EKF) method is proposed and evaluated through field tests on an experimental IWM-EV Experimental results show the ability of a proposed observer to provide accurate estimation Moreover, using the estimated sideslip angle and tire cornering stiffness, the vehicle stability control system, making best use of the advantages of IMW-EVs with a steer-by-wire system, is proposed Computer simulation using Matlab/Simulink-Carsim and experiments are carried out to demonstrate the effectiveness of the proposed stability control system Practical application of lateral tire force sensors to vehicle control systems is discussed for future personal electric vehicles
264 citations
TL;DR: Novel methods for estimating sideslip angle and roll angle using real-time lateral tire force measurements, obtained from the multisensing hub units, for practical applications to vehicle control systems of in-wheel-motor-driven electric vehicles are proposed.
Abstract: Robust estimation of vehicle states (e.g., vehicle sideslip angle and roll angle) is essential for vehicle stability control applications such as yaw stability control and roll stability control. This paper proposes novel methods for estimating sideslip angle and roll angle using real-time lateral tire force measurements, obtained from the multisensing hub units, for practical applications to vehicle control systems of in-wheel-motor-driven electric vehicles. In vehicle sideslip estimation, a recursive least squares (RLS) algorithm with a forgetting factor is utilized based on a linear vehicle model and sensor measurements. In roll angle estimation, the Kalman filter is designed by integrating available sensor measurements and roll dynamics. The proposed estimation methods, RLS-based sideslip angle estimator, and the Kalman filter are evaluated through field tests on an experimental electric vehicle. The experimental results show that the proposed estimator can accurately estimate the vehicle sideslip angle and roll angle. It is experimentally confirmed that the estimation accuracy is improved by more than 50% comparing to conventional method's one (see rms error shown in Fig. 4). Moreover, the feasibility of practical applications of the lateral tire force sensors to vehicle state estimation is verified through various test results.
218 citations
TL;DR: In this article, a new coordination scheme based on optimal guaranteed cost control technique by coordinating active front steering and direct yaw moment control is proposed, considering the uncertainty of tyre cornering stiffness due to the frequent variation of running conditions.
Abstract: Considering the uncertainty of tyre cornering stiffness due to the frequent variation of running conditions, a new coordination scheme is proposed based on optimal guaranteed cost control technique by coordinating active front steering and direct yaw moment control. A general procedure to develop an optimal guaranteed cost coordination controller (OGCC) is presented, and the effect of uncertainty deviation magnitude on the control system is discussed. An optimal coordination (OC) scheme based on LQR is also presented. Many simulations are carried out on an 8-DOF nonlinear vehicle model for a slalom manoeuvre and a lane-change manoeuvre, respectively. The simulation results show that the OGCC scheme has superior stability and tracking performances at different running conditions compared with the OC scheme.
198 citations
Cites background from "Development and Experimental Evalua..."
...About slip angle estimation algorithms, the readers can refer to [1,21,22]; however, it is assumed that the slip angle can be obtained directly in this paper....
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References
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Book•
31 Oct 2005
TL;DR: In this paper, the authors present a mean value model of SI and Diesel engines, and design and analysis of passive and active automotive suspension components, as well as semi-active and active suspensions.
Abstract: 1. Introduction.- 2.Lateral Vehicle Dynamics.- 3. Steering Control For Automated Lane Keeping.- 4. Longitudinal Vehicle Dynamics.- 5. Introduction to Longitudinal Control.- 6. Adaptive Cruise Control.- 7. Longitudinal Control for Vehicle Platoons.- 8. Electronic Stability Control.- 9. Mean Value Modeling Of SI and Diesel Engines.- 10. Design and Analysis of Passive Automotive Suspensions.- 11. Active Automotive Suspensions.-12. Semi-Active Suspensions.- 13. Lateral and Longitudinal Tires Forces.- 14. Tire-Road Friction Measurement on Highway Vehicles.- 15. Roll Dynamics and Rollover Prevention.- 16. Dynamics and Control of Hybrid Gas Electric Vehicles.
3,669 citations
"Development and Experimental Evalua..." refers background in this paper
...V EHICLE stability control systems that prevent vehicles from spinning, drifting out, and rolling over have been developed and recently commercialized by several automotive manufacturers [1]–[3]....
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...The slip angle of a tire is the angle of the velocity vector at the tire with the orientation of the tire [1]....
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...In such cases, the control system attempts to ensure that the actual yaw rate of the vehicle tracks a desired yaw rate determined by the driver’s steering input [1]....
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...However, in situations on low-friction road surfaces, it is also beneficial to control the vehicle slip angle preventing it from becoming too large, in addition to controlling yaw rate [1]–[3]....
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Book•
01 Feb 1992TL;DR: In this article, the authors attempt to find a middle ground by balancing engineering principles and equations of use to every automotive engineer with practical explanations of the mechanics involved, so that those without a formal engineering degree can still comprehend and use most of the principles discussed.
Abstract: This book attempts to find a middle ground by balancing engineering principles and equations of use to every automotive engineer with practical explanations of the mechanics involved, so that those without a formal engineering degree can still comprehend and use most of the principles discussed. Either as an introductory text or a practical professional overview, this book is an ideal reference.
3,166 citations
Book•
13 Dec 1978
TL;DR: In this article, the authors present an approach to the prediction of normal pressure distribution under a track and a simplified method for analysis of tracked vehicle performance, based on the Cone Index.
Abstract: Preface. Preface to the Third Edition. Preface to the Second Edition. Preface to the First Edition. Conversion Factors. Nomenclature. Introduction. 1. MECHANICS OF PNEUMATIC TIRES. 1.1 Tire Forces and Moments. 1.2 Rolling Resistance of Tires. 1.3 Tractive (Braking) Effort and Longitudinal Slip (Skid). 1.4 Cornering Properties of Tires. 1.4.1 Slip Angle and Cornering Force. 1.4.2 Slip Angle and Aligning Torque. 1.4.3 Camber and Camber Thrust. 1.4.4 Characterization of Cornering Behavior of. Tires. 1.5 Performance of Tires on Wet Surfaces. 1.6 Ride Properties of Tires. References. Problems. 2. MECHANICS OF VEHICLE-TERRAIN INTERACTION--TERRAMECHANICS. 2.1 Distribution of Stresses in the Terrain Under Vehicular Loads. 2.2 Applications of the Theory of Plastic Equilibrium to the Mechanics of Vehicle--Terrain Interaction. 2.3 Empirical Methods for Predicting Off-Road Vehicle Performance. 2.3.1 Empirical Methods Based on the Cone Index. 2.3.2 Empirical Methods Based on the Mean Maximum Pressure. 2.4 Measurement and Characterization of Terrain Response. 2.4.1 Characterization of Pressure-Sinkage Relationship. 2.4.2 Characterization of the Response to Repetitive Loading. 2.4.3 Characterization of the Shear Stress-Shear Displacement Relationship. 2.5 A Simplified Method for Analysis of Tracked Vehicle Performance. 2.5.1 Motion Resistance of a Track. 2.5.2 Tractive Effort and Slip of a Track. 2.6 A Computer-Aided Method for Evaluating the Performance of Vehicles with Flexible Tracks. 2.6.1 Approach to the Prediction of Normal Pressure Distribution under a Track. 2.6.2 Approach to the Prediction of Shear Stress Distribution under a Track. 2.6.3 Prediction of Motion Resistance and Drawbar Pull as Functions of Track Slip. 2.6.4 Experimental Substantiation. 2.6.5 Applications to Parametric Analysis and Design Optimization. 2.7 A Computer-Aided Method for Evaluating the Performance of Vehicles with Long-Pitch Link Tracks. 2.7.1 Basic Approach. 2.7.2 Experimental Substantiation. 2.7.3 Applications to Parametric Analysis and Design Optimization. 2.8 Methods for Parametric Analysis of Wheeled Vehicle Performance. 2.8.1 Motion Resistance of a Rigid Wheel. 2.8.2 Motion Resistance of a Pneumatic Tire. 2.8.3 Tractive Effort and Slip of a Wheel. 2.9 A Computer-Aided Method for Evaluating the Performance of Off-Road Wheeled Vehicles. 2.9.1 Basic Approach. 2.9.2 Experimental Substantiation. 2.9.3 Applications to Parametric Analysis. 2.10 Finite Element and Discrete Element Methods for the Study of Vehicle-Terrain Interaction. 2.10.1 The Finite Element Method. 2.10.2 The Discrete (Distinct) Element Method. References. Problems. 3. PERFORMANCE CHARACTERISTICS OF ROAD VEHICLES. 3.1 Equation of Motion and Maximum Tractive Effort. 3.2 Aerodynamic Forces and Moments. 3.3 Vehicle Power Plant and Transmission Characteristics. 3.3.1 Internal Combustion Engines. 3.3.2 Electric Drives. 3.3.3 Hybrid Drives. 3.3.4 Fuel Cells. 3.3.5 Transmission Characteristics. 3.4 Vehicle Power Plant and Transmission Characteristics. 3.4.1 Power Plant Characteristics. 3.4.2 Transmission Characteristics. 3.5 Prediction of Vehicle Performance. 3.5.1 Acceleration Time and Distance. 3.5.2 Gradability. 3.6 Operating Fuel Economy. 3.7 Engine and Transmission Matching. 3.8 Braking Performance. 3.8.1 Braking Characteristics of a Two-Axle. Vehicle. 3.8.2 Braking Efficiency and Stopping Distance. 3.8.3 Braking Characteristics of a Tractor-Semitrailer. 3.8.4 Antilock Brake Systems. 3.8.5 Traction Control Systems. References. Problems. 4. PERFORMANCE CHARACTERISTICS OF OFF-ROAD VEHICLES. 4.1 Drawbar Performance. 4.1.1 Drawbar Pull and Drawbar Power. 4.1.2 Tractive Efficiency. 4.1.3 Four Wheel Drive. 4.1.5 Coefficient of Traction. 4.1.4 Weight-to-Power Ratio for Off-Road Vehicles. 4.2 Fuel Economy of Cross-Country Operations. 4.3 Transport Productivity and Transport Efficiency. 4.4 Mobility Map and Mobility Profile. 4.5 Selection of Vehicle Configurations for Off-Road Operations. References. Problems. 5. HANDLING CHARACTERISTICS OF ROAD VEHICLES. 5.1 Steering Geometry. 5.2 Steady-State Handling Characteristics of a Two-Axle Vehicle. 5.2.1 Neutral Steer. 5.2.2 Understeer. 5.2.3 Oversteer. 5.3 Steady-State Response to Steering Input. 5.3.1 Yaw Velocity Response. 5.3.2 Lateral Acceleration Response. 5.3.3 Curvature Response. 5.4 Testing of Handling Characteristics. 5.4.1 Constant Radius Test. 5.4.2 Constant Speed Test. 5.4.3 Constant Steer Angle Test. 5.5 Transient Response Characteristics. 5.6 Directional Stability. 5.6.1 Criteria for Directional Stability. 5.6.2 Vehicle Stability Control. 5.7 Steady-State Handling Characteristics of a Tractor-Semitrailer. 5.8 Simulation Models for the Directional Behavior of Articulated Road Vehicles. References. Problems. 6. STEERING OF TRACKED VEHICLES. 6.1 Simplified Analysis of the Kinetics of Skid-Steering. 6.2 Kinematics of Skid-Steering. 6.3 Skid-Steering at High Speeds. 6.4 A General Theory for Skid-Steering on Firm Ground. 6.4.1 Shear Displacement on the Track-Ground Interface. 6.4.2 Kinetics in a Steady-State Turning Maneuver. 6.4.3 Experimental Substantiation. 6.4.4 Coefficient of Lateral Resistance. 6.5 Power Consumption of Skid-Steering. 6.6 Steering Mechanisms for Tracked Vehicles. 6.6.1 Clutch/Brake Steering System. 6.6.2 Controlled Differential Steering System. 6.6.3 Planetary Gear Steering System. 6.7 Articulated Steering. References. Problems. 7. VEHICLE RIDE CHARACTERISTICS. 7.1 Human Response to Vibration. 7.1.1 International Standard ISO 2631-1:1985. 7.1.2 International Standard ISO 2631-1:1997. 7.2 Vehicle Ride Models. 7.2.1 Two-Degree-of-Freedom Vehicle Model for Sprung and Unsprung Mass. 7.2.2 Numerical Methods for Determining the Response of a Quarter-Car Model to Irregular Surface Profile Excitation. 7.2.3 Two-Degree-of-Freedom Vehicle Model for Pitch and Bounce. 7.3 Introduction to Random Vibration. 7.3.1 Surface Elevation Profile as a Random Function. 7.3.2 Frequency Response Function. 7.3.3 Evaluation of Vehicle Vibration in Relation to the Ride Comfort Criterion. 7.4 Active and Semi-Active Suspensions. References. Problems. 8. INTRODUCTION TO AIR-CUSHION VEHICLES. 8.1 Air-Cushion Systems and Their Performance. 8.1.1 Plenum Chamber. 8.1.2 Peripheral Jet. 8.2 Resistance of Air-Cushion Vehicles. 8.3 Suspension Characteristics of Air-Cushion Systems. 8.3.1 Heave (or Bounce) Stiffness. 8.3.2 Roll Stiffness. 8.4 Directional Control of Air-Cushion Vehicles. References. Problems. Index.
2,930 citations
Book•
01 Dec 2010TL;DR: This advanced tutorial will describe the GPS signals, the various measurements made by the GPS receivers, and estimate the achievable accuracies, and focus on topics which are more unique to radio navigation or GPS.
Abstract: The Global Positioning System (GPS) is a satellite-based navigation and time transfer system developed by the U.S. Department of Defense. It serves marine, airborne, and terrestrial users, both military and civilian. Specifically, GPS includes the Standard Positioning Service (SPS) which provides civilian users with 100 meter accuracy, and it serves military users with the Precise Positioning Service (PPS) which provides 20-m accuracy. Both of these services are available worldwide with no requirement for a local reference station. In contrast, differential operation of GPS provides 2- to 10-m accuracy to users within 1000 km of a fixed GPS reference receiver. Finally, carrier phase comparisons can be used to provide centimeter accuracy to users within 10 km and potentially within 100 km of a reference receiver. This advanced tutorial will describe the GPS signals, the various measurements made by the GPS receivers, and estimate the achievable accuracies. It will not dwell on those aspects of GPS which are well known to those skilled in the radio communications art, such as spread-spectrum or code division multiple access. Rather, it will focus on topics which are more unique to radio navigation or GPS. These include code-carrier divergence, codeless tracking, carrier aiding, and narrow correlator spacing.
2,203 citations