Active Kinematics Suspension Integrating Milliken Moment Method in the Control Logic

2016 ◽  
Author(s):  
Isabel Ramirez Ruiz ◽  
Edoardo Sabbioni ◽  
Federico Cheli
Keyword(s):  
Vehicle Dynamics ◽  
Moment Method ◽  
Full Range ◽  
Operating Conditions ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Slip Angle ◽  
Control Logic ◽  
Sideslip Angle ◽  
Vehicle Dynamics Control

The idea behind the active kinematics suspension is to enhance its performance of vehicle dynamics. This includes improve steady and dynamic limit stability and faster transient reaction through optimized lateral and longitudinal dynamics. The driver’s benefits are: improved safety and higher driving pleasure. To achieve more control over the position of the rear wheels and thus the tire contact patch on the ground, the active suspension introduces one independent linear actuator at each rear wheel that controls the wheels’ camber freely. This paper will present the vehicle dynamics control logic methodology of a rear active vehicle suspension implementing the Milliken Moment Method (MMM) diagram to improve the vehicle stability and controllability, achieving gradually the front and rear axle limits. A Multibody vehicle model has been used to achieve a high fidelity simulation to generate the Milliken Moment Diagram (MMD) also known as the CN-AY diagram, where the vehicle’s yaw moment coefficient (CN) about the CG versus its lateral acceleration (AY) is mapped for different vehicle sideslip angle and steering wheel angles. With the Moment Method computer program it is possible to create the limit of the diagram over the full range of steering wheel angle and side slip angle for numerous changes in vehicle configuration of rear camber wheels and operating conditions. The vehicle dynamics control logic uses the maps like a vehicle maneuvering area under different vehicle active configurations where vehicle’s control is most fundamentally expressed as a yawing moment to quantify the directional stability.

Development of a Vehicle Dynamics Control System for Four In-Wheel Motor EV

2013 ◽  
Vol 427-429 ◽  
pp. 1346-1349 ◽  
Author(s):  
Lu Xiong ◽  
Fen Miao Shi ◽  
Shen Lin Hu ◽  
Yuan Feng
Keyword(s):  
Control System ◽  
Vehicle Dynamics ◽  
Reference Value ◽  
Operating Conditions ◽  
Lateral Acceleration ◽  
Critical Conditions ◽  
Normal Operating ◽  
Physical Limit ◽  
Acceleration Feedback ◽  
Vehicle Dynamics Control

This paper describes the design of a vehicle dynamics control system for improving handling and stability of electric vehicle. A vehicle with this control system can facilitate good handling performance under normal operating conditions and enhance stability under critical conditions. A feedforward and a feedback controllers are employed to make the vehicle follow the reference yaw rate based on a non-linear 5DOF vehicle model under normal operating conditions. When the tire tends to reach physical limit, the reference value will be modified with lateral acceleration feedback. Finally, simulation is conducted under several standard maneuvers and the results verify the effectiveness of the proposed control system.

Test Results: Vehicle Responses to Simulated Drag Caused by Front Tire Tread Detachment — The Effect of Scrub Radius and Speed

2018 ◽  
Author(s):  
Mark W. Arndt ◽  
Stephen M. Arndt
Keyword(s):  
Lateral Displacement ◽  
Rear Wheel ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Slip Angle ◽  
Yaw Rate ◽  
Wheel Drive ◽  
Steady State Responses ◽  
Four Wheel Drive ◽  
Left Front

The effects of reduced kingpin offset distance at the ground (scrub radius) and speed were evaluated under controlled test conditions simulating front tire tread detachment drag. While driving in a straight line at target speeds of 50, 60, or 70 mph with the steering wheel locked, the drag of a tire tread detachment was simulated by applying the left front brake with a pneumatic actuator. The test vehicle was a 2001 dual rear wheel four-wheel-drive Ford F350 pickup truck with an 11,500 lb. GVWR. The scrub radius was tested at the OEM distance of 125 mm (Δ = 0) and at reduced distances of 49 mm (Δ = −76) and 11 mm (Δ = −114). The average steady state responses at 70 mph with the OEM scrub radius were: steering torque = −24.5 in-lb; slip angle = −3.8 deg; lateral acceleration = −0.47 g; yaw rate = −8.9 deg/sec; lateral displacement after 0.75 seconds = 3.1 ft and lateral displacement after 1.5 seconds = 13.1 ft. At the OEM scrub radius, responses that increased linearly with speed included: slip angle (R2 = 0.84); lateral acceleration (R2 = 0.93); yaw rate (R2 = 0.73) and lateral displacement (R2 = 0.59 and R2 = 0.87, respectively). At the OEM scrub radius, steer torque decreased linearly with speed (R2 = 0.76) and longitudinal acceleration had no linear relationship with speed (R2 = 0.09). At 60 mph and 70 mph for both scrub radius reductions, statistically significant decreases (CI ≥ 95%) occurred in average responses of steer torque, slip angle, lateral acceleration, yaw rate, and lateral displacement. At 50 mph, reducing the OEM scrub radius to 11 mm resulted in statistically significant decreases (CI ≥ 95%) in average responses of steer torque, lateral acceleration, yaw rate and lateral displacement. At 50 mph the average slip angle response decreased (CI = 87%) when the OEM scrub radius was reduced to 11 mm.

Analysis of Vehicle Lateral Response During Regenerative Braking in a Turn

2016 ◽  
Author(s):  
C. S. Nanda Kumar ◽  
Shankar C. Subramanian
Keyword(s):  
Rear Wheel ◽  
Front Wheel ◽  
Lateral Acceleration ◽  
Regenerative Braking ◽  
Steering Wheel ◽  
Slip Angle ◽  
Lateral Response ◽  
Wheel Drive ◽  
Reference Track ◽  
The Impact

Regenerative braking is applied only at the driven wheels in electric and hybrid vehicles. The presence of brake force only at the driven wheels reduces the lateral traction limit of the corresponding tires. This impacts the vehicle lateral response, particularly while applying the regenerative brake in a turn. In this paper, a detailed study was made on the impact of regenerative brake on the vehicle lateral response in front wheel drive and rear wheel drive configurations on dry and wet asphalt road surfaces. Simulations were done considering a typical set of vehicle parameters with the IPG CarMaker® software for different drive conditions and braking configurations along the same reference track. The steering wheel angle, yaw rate, lateral acceleration, vehicle slip angle, and tire forces were obtained. Further, they were compared against the conventional all wheel friction brake configuration. The regenerative braking configuration that had the most impact on vehicle lateral response was analyzed and response variations were quantified.

Validation of a non-linear vehicle dynamics simulation for limit handling

2002 ◽  
Vol 216 (4) ◽  
pp. 319-327 ◽  
Author(s):  
R Wade-Allen ◽  
J P Chrstos ◽  
G Howe ◽  
D H Klyde ◽  
T J Rosenthal
Keyword(s):  
Vehicle Dynamics ◽  
Normal Load ◽  
Full Range ◽  
Operating Regime ◽  
Operating Conditions ◽  
Dynamics Simulation ◽  
Passenger Cars ◽  
Power Train ◽  
Ground Vehicle ◽  
Dynamic Operating

This paper discusses the validation of a ground vehicle dynamics computer simulation that includes complete models for sprung and unsprung masses, tyres, suspension, steering and brake systems, and power train including engine, transmission and differentials. The models have been developed over the last decade and have been applied to single-unit passenger cars, trucks and buses, and articulated tractor/trailer vehicles up to limit performance operating conditions. The tyre and vehicle models use composite parameters that are relatively easy to measure. However, the measurements must cover the key operating regime where the simulation is expected to be applied. For example, limit performance manoeuvring conditions require tyre data over large slip conditions and high normal load (beyond the design load) to cover the full range of dynamic operating conditions. Spring and damper response should also take into account large deflections and high velocities respectively to cover relevant non-linearities.

Ranking Tires for Heavy Truck Steering Feel Performance Using a Simulation Model2

2006 ◽  
Vol 34 (1) ◽  
pp. 64-82 ◽  
Author(s):  
S. L. Haas
Keyword(s):  
Vehicle Dynamics ◽  
Performance Metrics ◽  
Steering System ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Dynamics Model ◽  
Objective Testing ◽  
Steering Feel ◽  
Wheel Torque ◽  
Heavy Truck

Abstract The effects of seven different tire sets on heavy truck steering feel characteristics were demonstrated from objective testing. Also, the steering behavior and vehicle dynamics were modeled in order to determine how well the resulting simulations could rank the steering performance of the tire sets relative to the objective results. The objective testing was performed using a 6×4 tractor with a two-axle flatbed semi-trailer. Measured data included steering wheel torque, steering wheel angle, and lateral acceleration behavior resulting from on-center-type steering tests. In addition, the hydraulic pressure from the power steering system was also measured. The tests consisted of multiple cycles at 0.2 Hz and ±0.2 g. Steering-related performance metrics were selected and calculated based on the interaction between measured parameters. The same test procedure was also applied using an analytical model of a steering system. The input was steering wheel torque, and outputs included the road wheel angles at the steer axle, which were then fed into a commercial vehicle dynamics model providing the vehicle dynamics behavior along with feedback required for the steering model (e.g., king pin moments). Tire loads and slip angles were also provided by the vehicle dynamics model and used as input to a tire model predicting tire force and moment behavior. The related metrics were subsequently computed and compared to the measured results. Effects of the different tire sets on steering characteristics were seen from both the objective and simulation tests. Seven performance metrics were applied in a ranking comparison between measured and modeled results. Correlation of the modeled to measured metrics ranged from R2 values of 0.40 to 0.99 for the seven metrics considered.

Integrating Inertial Sensors With Global Positioning System (GPS) for Vehicle Dynamics Control

2004 ◽  
Vol 126 (2) ◽  
pp. 243-254 ◽  
Author(s):  
Jihan Ryu ◽  
J. Christian Gerdes
Keyword(s):  
Global Positioning System ◽  
Vehicle Dynamics ◽  
Inertial Sensors ◽  
Longitudinal Velocity ◽  
Positioning System ◽  
Sideslip Angle ◽  
Global Positioning ◽  
Reduce Measurement Error ◽  
Gps System ◽  
Vehicle Dynamics Control

This paper demonstrates a method of estimating several key vehicle states—sideslip angle, longitudinal velocity, roll and grade—by combining automotive grade inertial sensors with a Global Positioning System (GPS) receiver. Kinematic Kalman filters that are independent of uncertain vehicle parameters integrate the inertial sensors with GPS to provide high update estimates of the vehicle states and the sensor biases. Using a two-antenna GPS system, the effects of pitch and roll on the measurements can be quantified and are demonstrated to be quite significant in sideslip angle estimation. Employing the same GPS system as an input to the estimator, this paper develops a method that compensates for roll and pitch effects to improve the accuracy of the vehicle state and sensor bias estimates. In addition, calibration procedures for the sensitivity and cross-coupling of inertial sensors are provided to further reduce measurement error. The resulting state estimates compare well to the results from calibrated models and Kalman filter predictions and are clean enough to use in vehicle dynamics control systems without additional filtering.

scholarly journals Vehicle Sideslip Angle Estimation Based on General Regression Neural Network

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Wang Wei ◽  
Bei Shaoyi ◽  
Zhang Lanchun ◽  
Zhu Kai ◽  
Wang Yongzhi ◽  
...  
Keyword(s):  
Neural Network ◽  
Estimation Method ◽  
Stability Control ◽  
Lateral Acceleration ◽  
General Regression Neural Network ◽  
Slip Angle ◽  
Sideslip Angle ◽  
Training Samples ◽  
Stability Control System ◽  
General Regression

Aiming at the accuracy of estimation of vehicle’s mass center sideslip angle, an estimation method of slip angle based on general regression neural network (GRNN) and driver-vehicle closed-loop system has been proposed: regarding vehicle’s sideslip angle as time series mapping of yaw speed and lateral acceleration; using homogeneous design project to optimize the training samples; building the mapping relationship among sideslip angle, yaw speed, and lateral acceleration; at the same time, using experimental method to measure vehicle’s sideslip angle to verify validity of this method. Estimation results of neural network and real vehicle experiment show the same changing tendency. The mean of error is within 10% of test result’s amplitude. Results show GRNN can estimate vehicle’s sideslip angle correctly. It can offer a reference to the application of vehicle’s stability control system on vehicle’s state estimation.

Vehicle Sideslip Angle Estimation Through Neural Networks: Application to Experimental Data

2006 ◽  
Author(s):  
Stefano Melzi ◽  
Edoardo Sabbioni ◽  
Alessandro Concas ◽  
Marco Pesce
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Lateral Acceleration ◽  
Slip Angle ◽  
Vehicle Speed ◽  
Sideslip Angle ◽  
The Neural Network ◽  
Training Stage ◽  
Wide Range ◽  
Self Adaptation

This work explores the possibility of using a non-structured algorithm as a sideslip angle valuer: on the basis of a preliminary numerical analysis, a neural network was designed and trained with experimental signals of lateral acceleration, vehicle speed, yaw rate and steer angle. The network was applied to experimental data in order to verify its capability of self-adaptation to changes in friction coefficient and to provide accurate estimations for manoeuvres sensibly different from the ones used during the training stage. The simple architecture joined with an appropriate training set conferred good self-adaptation properties to the neural network which was able to provide satisfying estimation of side slip angle for a wide range of manoeuvres and different friction conditions.

scholarly journals Design of a Novel Nonlinear Observer to Estimate Sideslip Angle and Tire Forces for Distributed Electric Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Chuanxue Song ◽  
Feng Xiao ◽  
Shixin Song ◽  
Shaokun Li ◽  
Jianhua Li
Keyword(s):  
Electric Vehicle ◽  
Vehicle Dynamics ◽  
Unscented Kalman Filter ◽  
Lateral Force ◽  
Nonlinear Observer ◽  
Accurate Estimation ◽  
State Variables ◽  
Force Estimation ◽  
Sideslip Angle ◽  
Vehicle Dynamics Control

For four-wheel independently driven (4WD) distributed electric vehicle (DEV), vehicle dynamics control systems such as direct yaw moment control (DYC) can be easily achieved. Accurate estimation of vehicle state variables and uncertain parameters can improve the robustness of vehicle dynamics control system. Various sensors are generally equipped to the acquisition of the vehicle dynamics. For both technical and economic reasons, some fundamental vehicle parameters, such as the sideslip angle and tire-road forces, can hardly be obtained through sensors directly. Therefore, this paper presented a state observer to estimate these variables based on Unscented Kalman Filter (UKF). To improve the accuracy of UKF, measurement noise covariance is also self-adaptive regulated. In addition, a nonlinear dynamics tire model is utilized to improve the accuracy of tire lateral force estimation. The simulation and experiment results show that the proposed observer can provide the precision values of the vehicle state.

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