Model-Based Estimation for Vehicle Dynamics States at the Limit Handling

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Gang Jia ◽  
Liang Li ◽  
Dongpu Cao
Keyword(s):  
Performance Enhancement ◽  
Unscented Kalman Filter ◽  
Estimation Method ◽  
Dynamics Model ◽  
Sideslip Angle ◽  
Model Based ◽  
Speed Sensor ◽  
Proposed Model ◽  
Roll Rate ◽  
Lift Off

This technical brief proposes a new model-based estimation method for the vehicle sideslip angle, yaw rate, roll angle, and roll rate using unscented Kalman filter (UKF). Since a vehicle wheel could potentially lift off the ground during the limit handling, a switched vehicle roll dynamics model (wheel lift and no wheel lift) is developed and integrated within the proposed model-based estimation approach considering the availability of wheel speed sensor. The simulation results and analyses demonstrate the performance enhancement of the proposed estimation method over the method not considering wheel lift during the limit handling.

scholarly journals Reliable Sideslip Angle Estimation of Four-Wheel Independent Drive Electric Vehicle by Information Iteration and Fusion

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Te Chen ◽  
Long Chen ◽  
Xing Xu ◽  
Yingfeng Cai ◽  
Haobin Jiang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Estimation Method ◽  
Longitudinal Force ◽  
Recursive Least Squares ◽  
Accurate Estimation ◽  
Dynamics Model ◽  
Sideslip Angle ◽  
Angle Estimation ◽  
Kinematics Model ◽  
Model Based

Accurate estimation of longitudinal force and sideslip angle is significant to stability control of four-wheel independent driven electric vehicle. The observer design problem for the longitudinal force and sideslip angle estimation is investigated in this work. The electric driving wheel model is introduced into the longitudinal force estimation, considering the longitudinal force is the unknown input of the system, the proportional integral observer is applied to restructure the differential equation of longitudinal force, and the extended Kalman filter is utilized to estimate the unbiased longitudinal force. Using the estimated longitudinal force, considering the unknown disturbances and uncertainties of vehicle model, the robust sideslip angle estimator is proposed based on vehicle dynamics model. Moreover, the recursive least squares algorithm with forgetting factor is applied to vehicle state estimation based on the vehicle kinematics model. In order to integrate the advantages of the dynamics-model-based observer and kinematics-model-based observer and improve adaptability of observer system in complex working conditions, a vehicle sideslip angle fusion estimation strategy is proposed. The simulations and experiments are implemented and the performance of proposed estimation method is validated.

Real-time SOC Estimation of the EKF and UKF Algorithms Under Different Working Conditions

2021 ◽  
pp. 1-29
Author(s):  
Xiongbin Peng ◽  
Yuwu Li ◽  
Wei Yang ◽  
Akhil Garg
Keyword(s):  
Kalman Filter ◽  
Working Conditions ◽  
Unscented Kalman Filter ◽  
Stress Test ◽  
Estimation Method ◽  
Influential Factor ◽  
Recursive Least Squares ◽  
Maximum Deviation ◽  
Soc Estimation ◽  
Proposed Model

Abstract In the battery thermal management system (BMS), the state of charge (SOC) is a very influential factor, which can prevent overcharge and over-discharge of the lithium-ion battery (LIB). This paper proposed a battery modeling and online battery parameter identification method based on the Thevenin equivalent circuit model (ECM) and recursive least squares (RLS) algorithm. The proposed model proved to have high accuracy. The error between the ECM terminal voltage value and the actual value basically fluctuates between ±0.1V. The extended Kalman filter (EKF) algorithm and the unscented Kalman filter (UKF) algorithm were applied to estimate the SOC of the battery based on the proposed model. The SOC experimental results obtained under dynamic stress test (DST), federal urban driving schedule (FUDS), and US06 cycle conditions were analyzed. The maximum deviation of the SOC based on EKF was 1.4112%~2.5988%, and the maximum deviation of the SOC based on UKF was 0.3172%~0.3388%. The SOC estimation method based on UKF and RLS provides a smaller deviation and better adaptability in different working conditions, which makes it more implementable in a real-world automobile application.

scholarly journals SYSTEM DYNAMICS MODEL BASED ON EVOLUTIONARY GAME THEORY FOR QUALITY SUPERVISION AMONG CONSTRUCTION STAKEHOLDERS

2018 ◽  
Vol 24 (4) ◽  
pp. 318-330 ◽  
Author(s):  
Shengyu Guo ◽  
Pan Zhang ◽  
Jianying Yang
Keyword(s):  
Game Theory ◽  
System Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Model Based ◽  
Proposed Model ◽  
The Stability ◽  
The Impact

To address the gap, that is, few studies have explored the influence of the participants’ interactions with one another during construction quality supervision, this paper proposes a system dynamics model based on evolutionary game theory to describe the complex and dynamic interactions among tripartite stakeholders in China, including the project owner (PO), construction supervising engineer (CSE), and construction contractor (CC). First, the replicated dynamic equation set is established in terms of expense targets. Second, the equilibrium solutions of the equation set are obtained to test strategy options. The trends of system fluctuations caused by penalty and reward changes are also analyzed. Finally, the stability of the proposed model is improved by integrating a dynamic penalty–reward scenario into the evolutionary strategy of the PO. Simulation results show that: 1) the evolutionary stable strategy does not exist in initial interactions, 2) the degrees of penalty and reward considerably affect the CC’s rate variable, and 3) the dynamic penalty–reward scenario could effectively improve the stability of the proposed model. The unsteadiness of the quality supervision system and the stability control scenario could help in understanding the impact of interactions among stakeholders and provide suggestions for optimizing quality supervision procedures.

scholarly journals On co-estimation and validation of vehicle driving states by a UKF-based approach

2021 ◽  
Vol 12 (1) ◽  
pp. 19-30
Author(s):  
Peng Wang ◽  
Hui Pang ◽  
Zijun Xu ◽  
Jiamin Jin
Keyword(s):  
State Estimation ◽  
Degrees Of Freedom ◽  
Unscented Kalman Filter ◽  
Control Plant ◽  
Estimation Method ◽  
Lateral Acceleration ◽  
Accurate Information ◽  
Sideslip Angle ◽  
Safety Control ◽  
Vehicle State Estimation

Abstract. It is necessary to acquire the accurate information of vehicle driving states for the implementation of automobile active safety control. To this end, this paper proposes an effective co-estimation method based on an unscented Kalman filter (UKF) algorithm to accurately predict the sideslip angle, yaw rate, and longitudinal speed of a ground vehicle. First, a 3 degrees-of-freedom (DOFs) nonlinear vehicle dynamics model is established as the nominal control plant. Then, based on CarSim software, the simulation results of the front steer angle and longitudinal and lateral acceleration are obtained under a variety of working conditions, which are regarded as the pseudo-measured values. Finally, the joint simulation of vehicle state estimation is realized in the MATLAB/Simulink environment by using the pseudo-measured values and UKF algorithm concurrently. The results show that the proposed UKF-based vehicle driving state estimation method is effective and more accurate in different working scenarios compared with the EKF-based estimation method.

A Modified Dugoff Tire Model for Combined-slip Forces

2010 ◽  
Vol 38 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Nenggen Ding ◽  
Saied Taheri
Keyword(s):  
Vehicle Dynamics ◽  
Tire Model ◽  
Magic Formula ◽  
Model Based ◽  
Proposed Model ◽  
Road Friction ◽  
On Line ◽  
Double Lane Change ◽  
Tire Forces ◽  
Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

2020 ◽  
pp. 1-10
Author(s):  
Abdullah Genc
Keyword(s):  
Path Loss ◽  
Forest Area ◽  
Occupancy Rate ◽  
Loss Model ◽  
Path Loss Model ◽  
Model Based ◽  
Proposed Model ◽  
Pine Trees ◽  
Foliage Density ◽  
Reference Measurements

Abstract In this paper, a new empirical path loss model based on frequency, distance, and volumetric occupancy rate is generated at the 3.5 and 4.2 GHz in the scope of 5G frequency bands. This study aims to determine the effect of the volumetric occupancy rate on path loss depending on the foliage density of the trees in the pine forest area. Using 4.2 GHz and the effect of the volumetric occupancy rate contributes to the literature in terms of novelty. Both the reference measurements to generate a model and verification measurements to verify the proposed models are conducted in three different regions of the forest area with double ridged horn antennas. These regions of the artificial forest area consist of regularly sorted and identical pine trees. Root mean square error (RMSE) and R-squared values are calculated to evaluate the performance of the proposed model. For 3.5 and 4.2 GHz, while the RMSEs are 3.983 and 3.883, the values of R-squared are 0.967 and 0.963, respectively. Additionally, the results are compared with four path loss models which are commonly used in the forest area. The proposed one has the best performance among the other models with values 3.98 and 3.88 dB for 3.5 and 4.2 GHz.

scholarly journals Lane Departure Warning Estimation Using Yaw Acceleration

2020 ◽  
Vol 11 (1) ◽  
pp. 102-111
Author(s):  
Em Poh Ping ◽  
J. Hossen ◽  
Wong Eng Kiong
Keyword(s):  
Vehicle Dynamics ◽  
Dynamic Responses ◽  
Dynamics Simulation ◽  
Steering Wheel ◽  
Mathematical Representation ◽  
Vehicle Speed ◽  
Lane Departure Warning ◽  
Model Based ◽  
Lane Departure ◽  
Proposed Model

AbstractLane departure collisions have contributed to the traffic accidents that cause millions of injuries and tens of thousands of casualties per year worldwide. Due to vision-based lane departure warning limitation from environmental conditions that affecting system performance, a model-based vehicle dynamics framework is proposed for estimating the lane departure event by using vehicle dynamics responses. The model-based vehicle dynamics framework mainly consists of a mathematical representation of 9-degree of freedom system, which permitted to pitch, roll, and yaw as well as to move in lateral and longitudinal directions with each tire allowed to rotate on its axle axis. The proposed model-based vehicle dynamics framework is created with a ride model, Calspan tire model, handling model, slip angle, and longitudinal slip subsystems. The vehicle speed and steering wheel angle datasets are used as the input in vehicle dynamics simulation for predicting lane departure event. Among the simulated vehicle dynamic responses, the yaw acceleration response is observed to provide earlier insight in predicting the future lane departure event compared to other vehicle dynamics responses. The proposed model-based vehicle dynamics framework had shown the effectiveness in estimating lane departure using steering wheel angle and vehicle speed inputs.

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