Actuator Fault Sensitivity Analysis for In-Wheel Motor Electric Ground Vehicle With Active Steering System

2014 ◽  
Author(s):  
Guoguang Zhang ◽  
Hui Zhang ◽  
Junmin Wang ◽  
Hai Yu ◽  
Roger Graaf
Keyword(s):  
Direct Method ◽  
Equilibrium Points ◽  
Longitudinal Velocity ◽  
Steering System ◽  
Sensitivity Analyses ◽  
Actuator Faults ◽  
Lateral Velocity ◽  
Sideslip Angle ◽  
Ground Vehicle ◽  
Additive Loss

This paper presents the sensitivity analyses on vehicle motions with regard to faults of in-wheel motors and steering motor for an electric ground vehicle (EGV) with independently actuated in-wheel rear motors. Based on the vehicle model, direct method is applied to determine, to what extent, that different actuator faults affect vehicle motions such as the longitudinal velocity, lateral velocity, and yaw rate. For motion indices like vehicle sideslip angle and longitudinal acceleration, linearizations around equilibrium points are conducted and their sensitivities to actuator faults are analyzed. Results show that all mentioned vehicle motions are more sensitive to the fault of steering motor than that of in-wheel motors. In addition, the effects on vehicle motions due to four types of faults, i.e. additive, loss-of-effectiveness, time-varying-gain and stuck-at-fixed-level faults, are examined through CarSim® simulations and vehicle experiments under a representative maneuver.

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

2019 ◽  
Vol 234 (3) ◽  
pp. 338-348
Author(s):  
Hui Jing ◽  
Rongrong Wang ◽  
Cong Li ◽  
Jinxiang Wang
Keyword(s):  
Electric Vehicles ◽  
Measurement Problem ◽  
Low Cost ◽  
Steering System ◽  
Front Wheel ◽  
Steering Control ◽  
Lateral Velocity ◽  
Lateral Dynamics ◽  
Vehicle Rollover ◽  
Differential Steering

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

scholarly journals Vehicle Sideslip Angle Estimation Using Two Single-Antenna GPS Receivers

2010 ◽  
Author(s):  
Jong-Hwa Yoon ◽  
Huei Peng
Keyword(s):  
Low Cost ◽  
Longitudinal Velocity ◽  
Stability Control ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Sideslip Angle ◽  
Gps Receivers ◽  
Single Antenna ◽  
Active Safety Systems ◽  
Safety Systems

Knowing vehicle sideslip angle accurately is critical for active safety systems such as Electronic Stability Control (ESC). Vehicle sideslip angle can be measured through optical speed sensors, or dual-antenna GPS. These measurement systems are costly (∼$5k to $100k), which prohibits wide adoption of such systems. This paper demonstrates that the vehicle sideslip angle can be estimated in real-time by using two low-cost single-antenna GPS receivers. Fast sampled signals from an Inertial Measurement Unit (IMU) compensate for the slow update rate of the GPS receivers through an Extended Kalman Filter (EKF). Bias errors of the IMU measurements are estimated through an EKF to improve the sideslip estimation accuracy. A key challenge of the proposed method lies in the synchronization of the two GPS receivers, which is achieved through an extrapolated update method. Analysis reveals that the estimation accuracy of the proposed method relies mainly on vehicle yaw rate and longitudinal velocity. Experimental results confirm the feasibility of the proposed method.

Understanding the Lateral Dimension of Traffic: Measuring and Modeling Lane Discipline

2021 ◽  
pp. 036119812110318
Author(s):  
Rafael Delpiano
Keyword(s):  
New Technologies ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Lateral Position ◽  
Multiple Cameras ◽  
Lateral Velocity ◽  
Lane Changing ◽  
Lateral Dimension ◽  
Vehicle Position ◽  
Longitudinal Position

There is growing interest in understanding the lateral dimension of traffic. This trend has been motivated by the detection of phenomena unexplained by traditional models and the emergence of new technologies. Previous attempts to address this dimension have focused on lane-changing and non-lane-based traffic. The literature on vehicles keeping their lanes has generally been limited to simple statistics on vehicle position while models assume vehicles stay perfectly centered. Previously the author developed a two-dimensional traffic model aiming to capture such behavior qualitatively. Still pending is a deeper, more accurate comprehension and modeling of the relationships between variables in both axes. The present paper is based on the Next Generation SIMulation (NGSIM) datasets. It was found that lateral position is highly dependent on the longitudinal position, a phenomenon consistent with data capture from multiple cameras. A methodology is proposed to alleviate this problem. It was also discovered that the standard deviation of lateral velocity grows with longitudinal velocity and that the average lateral position varies with longitudinal velocity by up to 8 cm, possibly reflecting greater caution in overtaking. Random walk models were proposed and calibrated to reproduce some of the characteristics measured. It was determined that drivers’ response is much more sensitive to the lateral velocity than to position. These results provide a basis for further advances in understanding the lateral dimension. It is hoped that such comprehension will facilitate the design of autonomous vehicle algorithms that are friendlier to both passengers and the occupants of surrounding vehicles.

scholarly journals Development of PM<sub>2.5</sub> source impact spatial fields using a hybrid source apportionment air quality model

2015 ◽  
Vol 8 (7) ◽  
pp. 2153-2165 ◽  
Author(s):  
C. E. Ivey ◽  
H. A. Holmes ◽  
Y. T. Hu ◽  
J. A. Mulholland ◽  
A. G. Russell
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Large Scale ◽  
Major Ions ◽  
Current Knowledge ◽  
Direct Method ◽  
Hybrid Approach ◽  
Sensitivity Analyses ◽  
Adjustment Factors ◽  
The Impact

Abstract. An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). There is also a growing desire to directly use source impact estimates in health studies; however, source impacts cannot be directly measured. Several limitations are inherent in most source apportionment methods motivating the development of a novel hybrid approach that is used to estimate source impacts by combining the capabilities of receptor models (RMs) and chemical transport models (CTMs). The hybrid CTM–RM method calculates adjustment factors to refine the CTM-estimated impact of sources at monitoring sites using pollutant species observations and the results of CTM sensitivity analyses, though it does not directly generate spatial source impact fields. The CTM used here is the Community Multiscale Air Quality (CMAQ) model, and the RM approach is based on the chemical mass balance (CMB) model. This work presents a method that utilizes kriging to spatially interpolate source-specific impact adjustment factors to generate revised CTM source impact fields from the CTM–RM method results, and is applied for January 2004 over the continental United States. The kriging step is evaluated using data withholding and by comparing results to data from alternative networks. Data withholding also provides an estimate of method uncertainty. Directly applied (hybrid, HYB) and spatially interpolated (spatial hybrid, SH) hybrid adjustment factors at withheld observation sites had a correlation coefficient of 0.89, a linear regression slope of 0.83 ± 0.02, and an intercept of 0.14 ± 0.02. Refined source contributions reflect current knowledge of PM emissions (e.g., significant differences in biomass burning impact fields). Concentrations of 19 species and total PM2.5 mass were reconstructed for withheld observation sites using HYB and SH adjustment factors. The mean concentrations of total PM2.5 at withheld observation sites were 11.7 (± 8.3), 16.3 (± 11), 8.59 (± 4.7), and 9.2 (± 5.7) μg m−3 for the observations, CTM, HYB, and SH predictions, respectively. Correlations improved for concentrations of major ions, including nitrate (CMAQ–DDM (decoupled direct method): 0.404, SH: 0.449), ammonium (CMAQ–DDM: 0.454, SH: 0.492), and sulfate (CMAQ–DDM: 0.706, SH: 0.730). Errors in simulated concentrations of metals were reduced considerably: 295 % (CMAQ–DDM) to 139 % (SH) for vanadium; and 1340 % (CMAQ–DDM) to 326 % (SH) for manganese. Errors in simulated concentrations of some metals are expected to remain given the uncertainties in source profiles. Species concentrations were reconstructed using SH results, and the error relative to observed concentrations was greatly reduced as compared to CTM-simulated concentrations. Results demonstrate that the hybrid method along with a spatial extension can be used for large-scale, spatially resolved source apportionment studies where observational data are spatially and temporally limited.

Effect of the Fish-Bone Dam Angle on the Flow Mechanisms of a Fish-Bone Type Dividing Dike

2020 ◽  
Vol 54 (3) ◽  
pp. 58-67
Author(s):  
Jia Ni ◽  
Linwei Wang ◽  
Xixian Chen ◽  
Luan Luan Xue ◽  
Isam Shahrour
Keyword(s):  
Water Level ◽  
Longitudinal Velocity ◽  
Flow Characteristics ◽  
Fish Bone ◽  
Flume Experiments ◽  
Lateral Velocity ◽  
Engineering Structures ◽  
Flow Mechanisms ◽  
River Training ◽  
Large Velocity Gradient

AbstractFish-bone type dividing dikes are river engineering structures used for river training and to protect a mid-channel bar from scour. The flow characteristics around fish-bone type dividing dikes are very complicated, especially near its fish-bone dam. To understand the flow and scour processes associated with fish-bone dams, this paper conducts a numerical simulation of flow characteristics for different fish-bone dam angles. Based on the Yudaizhou fish-bone type dividing dike of the Dongliu Waterway, a 3-D numerical model is established via Flow-3D to simulate the flow characteristics around a fish-bone type dividing dike, which is verified by flume experiments. Based on the results, the effects of different fish-bone dam angles on water level and velocity distribution are investigated. With increasing fish-bone dam angle, the longitudinal and lateral gradients of the water level gradually decreased, and the variation degree of the longitudinal velocity also decreased; however, the variation degree of the lateral velocity increased. Vortex areas formed around the fish-bone dam and the downstream zone of the dike. A large velocity gradient was found around the dike, and the downstream vortex area decreased with increasing fish-bone dam angle.

scholarly journals Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1242
Author(s):  
Jiangyi Lv ◽  
Hongwen He ◽  
Wei Liu ◽  
Yong Chen ◽  
Fengchun Sun
Keyword(s):  
Autonomous Vehicles ◽  
Estimation Error ◽  
Longitudinal Velocity ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Lateral Velocity ◽  
Empirical Correction ◽  
Vehicle Velocity ◽  
Wide Range

Accurate and reliable vehicle velocity estimation is greatly motivated by the increasing demands of high-precision motion control for autonomous vehicles and the decreasing cost of the required multi-axis IMU sensors. A practical estimation method for the longitudinal and lateral velocities of electric vehicles is proposed. Two reliable driving empirical judgements about the velocities are extracted from the signals of the ordinary onboard vehicle sensors, which correct the integral errors of the corresponding kinematic equations on a long timescale. Meanwhile, the additive biases of the measured accelerations are estimated recursively by comparing the integral of the measured accelerations with the difference of the estimated velocities between the adjacent strong empirical correction instants, which further compensates the kinematic integral error on short timescale. The algorithm is verified by both the CarSim-Simulink co-simulation and the controller-in-the-loop test under the CarMaker-RoadBox environment. The results show that the velocities can be accurately and reliably estimated under a wide range of driving conditions without prior knowledge of the tire-model and other unavailable signals or frequently changeable model parameters. The relative estimation error of the longitudinal velocity and the absolute estimation error of the lateral velocity are kept within 2% and 0.5 km/h, respectively.

Stability Regions of Vehicle Lateral Dynamics: Estimation and Analysis

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Yiwen Huang ◽  
Wei Liang ◽  
Yan Chen
Keyword(s):  
Load Transfer ◽  
Equilibrium Points ◽  
Longitudinal Velocity ◽  
Linearization Method ◽  
Stability Control ◽  
Stable Operation ◽  
Lateral Stability ◽  
Ground Vehicles ◽  
Stability Regions ◽  
Road Friction

Abstract A new method is proposed to estimate and analyze the vehicle lateral stability region, which provides a direct and intuitive demonstration for the safety and stability control of ground vehicles. Based on a four-wheel vehicle model and a nonlinear two-dimensional (2D) analytical LuGre tire model, a local linearization method is applied to estimate the vehicle lateral stability regions by analyzing the vehicle stability at each operation point on a phase plane, which includes but not limited to the equilibrium points. As the collections of all the locally stable operation points, the estimated stability regions are conservative because both vehicle and tire stability are simultaneously considered, which are especially important for characterizing the stability features of highly/fully automated ground vehicles (AGV). The obtained lateral stability regions can be well explained by the vehicle characteristics of oversteering and understeering in the context of vehicle handling stability. The impacts of vehicle lateral load transfer, longitudinal velocity, tire-road friction coefficient, and steering angle on the estimated stability regions are presented and discussed. To validate the correctness of the estimated stability regions, a case study by matlab/simulink and CarSim® co-simulation is presented and discussed.

Observer-based state-feedback robust control for path following of autonomous ground vehicles

2019 ◽  
Vol 234 (2) ◽  
pp. 222-239 ◽  
Author(s):  
Pengpeng Feng ◽  
Jianwu Zhang ◽  
Weimiao Yang
Keyword(s):  
State Feedback ◽  
Longitudinal Velocity ◽  
Path Following ◽  
Linear Matrix ◽  
Ground Vehicles ◽  
Parameter Uncertainties ◽  
Lateral Velocity ◽  
External Disturbances ◽  
Static State ◽  
Autonomous Ground Vehicles

In this article, a robust [Formula: see text] observer-based static state-feedback controller is designed for the path following of autonomous ground vehicles. The Takagi–Sugeno fuzzy modeling technique is used for modeling of vehicle dynamics with varying longitudinal velocity first. Then considering the high cost of direct lateral velocity measurement, an observer is designed to estimate the value of lateral velocity. Meanwhile, a robust controller is proposed to deal with the parameter uncertainties and external disturbances simultaneously, including the variation of the tire-cornering stiffness of both front and rear tires. Afterward, the condition of designing such an observer-based controller is transformed into the feasible problem of linear matrix inequalities. Numerical simulations using a high-fidelity and full vehicle model are performed based on a Carsim–Simulink joint platform. Simulation results under different conditions and comparison with other controller show that the proposed controller is effective irrespective of the variation in the road condition, the change in the vehicle longitudinal velocity and the external disturbances.

Active Four-Wheel Steering System for Zero Sideslip Angle and Lateral Acceleration Control

2003 ◽  
Vol 36 (14) ◽  
pp. 371-376
Author(s):  
Toshihiro Hiraoka ◽  
Osamu Nishihara ◽  
Hiromitsu Kumamoto
Keyword(s):  
Steering System ◽  
Lateral Acceleration ◽  
Sideslip Angle

scholarly journals Gap perception in bumblebees

2018 ◽  
Author(s):  
Sridhar Ravi ◽  
Olivier Bertrand ◽  
Tim Siesenop ◽  
Lea-Sophie Manz ◽  
Charlotte Doussot ◽  
...  
Keyword(s):  
Optic Flow ◽  
Physical Environment ◽  
Longitudinal Velocity ◽  
Flight Tunnel ◽  
Flight Path ◽  
Flight Trajectory ◽  
Lateral Velocity ◽  
Environmental Features ◽  
Aerial Navigation ◽  
Lateral Displacements

AbstractA number of insects fly over long distances below the natural canopy where the physical environment is highly cluttered consisting of obstacles of varying shape, size and texture. While navigating within such environments animals need to perceive and disambiguate environmental features that might obstruct their flight. The most elemental aspect of aerial navigation through such environments is gap identification and passability evaluation. We used bumblebees to seek insights into the mechanisms used for gap identification when confronted with an obstacle in their flight path and behavioral compensations employed to assess gap properties. Initially, bumblebee foragers were trained to fly though an unobstructed flight tunnel that led to a foraging chamber. After the bees were familiar with this situation, we placed a wall containing a gap that unexpectedly obstructed the flight path on a return trip to the hive. The flight trajectories of the bees as they approached the obstacle wall and traversed the gap were analyzed in order to evaluate their behavior as a function of the distance between the gap and a background wall that was placed behind the gap. Bumblebees initially decelerate when confronted with an unexpected obstacle. Deceleration was first noticed when the obstacle subtended around 35° on the retina but also depended on the properties of the gap. Subsequently the bees gradually traded off their longitudinal velocity to lateral velocity and approached the gap increasing lateral displacements and lateral velocity. Bumblebees shaped their flight trajectory depending on the salience of the gap, in our case, indicated by the optic flow contrast between the region within the gap and on the obstacle, which increases with decreasing distance between the gap and the background wall. As the optic flow contrast decreased the bees spent increasing time moving laterally across the obstacles. During these repeated lateral maneuvers the bees are likely assessing gap geometry and passability.

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