Unscented Kalman-filter to manage the handling-comfort trade-off of quarter-of-vehicle

2021 ◽  
pp. 014233122110317
Author(s):  
Alhelou Muhammed ◽  
Alexander Gavrilov I
Keyword(s):  
Kalman Filter ◽  
Control Strategy ◽  
Unscented Kalman Filter ◽  
Comfort Level ◽  
Vertical Acceleration ◽  
Trade Off ◽  
The Road ◽  
Intermediate Variable ◽  
Acceleration Signal ◽  
Car Suspension

This paper investigates managing the comfort-handling trade-off of a quarter car suspension system using a Kalman filter. Using the unscented Kalman filter, the adapted feedback input signal is extracted based on the vertical acceleration signals of the chassis and wheel. Considering the chassis acceleration signal as the primary feedback to maintain a required comfort level, it is continuously adapted to keep an acceptable level of road handling. Compared with the traditional methods, which rely on the combination of the two modes of comfort and handling through an intermediate variable to manage the contradiction, this method focuses on comfort and improves the process of the road handling automatically. The proposed strategy is evaluated using simulation in MATLAB and the results show the feasibility of this method in managing the handling-comfort trade-off. In addition, mathematical relationships that allow this control strategy to be derived were shown. Moreover, the effects of road disturbances amplitudes and road quality on the performance of the proposed control strategy were investigated. Furthermore, the performance of the proposed method is compared with that of the hybrid-hook and the results show the superiority of the proposed algorithm.

Body attitude control strategy based on road level for heavy rescue vehicles

2020 ◽  
pp. 095440702096616
Author(s):  
Hao Chen ◽  
Mingde Gong ◽  
Dingxuan Zhao ◽  
Jianxu Zhu
Keyword(s):  
Control Strategy ◽  
Attitude Control ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Vertical Acceleration ◽  
Inference System ◽  
The Road ◽  
Body Attitude

This paper proposes an attitude control strategy based on road level for heavy rescue vehicles. The strategy aims to address the problem of poor ride comfort and stability of heavy rescue vehicles in complex road conditions. Firstly, with the pressure of the suspension hydraulic cylinder chamber without a piston rod as the parameter, Takagi–Sugeno fuzzy controller classification and adaptive network-based fuzzy inference system controller classification are used to recognise the road level. Secondly, particle swarm optimisation is adopted to obtain the optimal parameters of the active suspension system of vehicle body attitude control under different road levels. Lastly, the parameters of the active suspension system are selected in accordance with the road level recognised in the driving process to improve the adaptive adjustment capability of the active suspension system at different road levels. Test results show that the root mean square values of vertical acceleration, pitch angle and roll angle of the vehicle body are reduced by 59.9%, 76.2% and 68.4%, respectively. This reduction improves the ride comfort and stability of heavy rescue vehicles in complex road conditions.

scholarly journals Integrated Comfort-Adaptive Cruise and Semi-Active Suspension Control for an Autonomous Vehicle: An LPV Approach

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 813
Author(s):  
Gia Quoc Bao Tran ◽  
Thanh-Phong Pham ◽  
Olivier Sename ◽  
Eduarda Costa ◽  
Péter Gáspár
Keyword(s):  
Autonomous Vehicle ◽  
Active Suspension ◽  
Suspension System ◽  
Comfort Level ◽  
Linear Matrix ◽  
Vertical Acceleration ◽  
Cruise Control ◽  
Control Approach ◽  
The Road ◽  
Suspension Control

This paper presents an integrated linear parameter-varying (LPV) control approach of an autonomous vehicle with an objective to guarantee driving comfort, consisting of cruise and semi-active suspension control. First, the vehicle longitudinal and vertical dynamics (equipped with a semi-active suspension system) are presented and written into LPV state-space representations. The reference speed is calculated online from the estimated road type and the desired comfort level (characterized by the frequency weighted vertical acceleration defined in the ISO 2631 norm) usingprecomputed polynomial functions. Then, concerning cruise control, an LPV H2 controller using a linear matrix inequality (LMI) based polytopic approach combined with the compensation of the estimated disturbance forces is developed to track the comfort-oriented reference speed. To further enhance passengers’ comfort, a decentralized LPV H2 controller for the semi-active suspension system is proposed, minimizing the effect of the road profile variations. The interaction with cruise control is achieved by the vehicle’s actual speed being a scheduling parameter for suspension control. To assess the strategy’s performance, simulations are conducted using a realistic nonlinear vehicle model validated from experimental data. The simulation results demonstrate the proposed approach’s capability to improve driving comfort.

scholarly journals A Modified Unscented Kalman Filter Combined with Ant Lion Optimization for Vehicle State Estimation

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Yixi Zhang ◽  
Jian Ma ◽  
Xuan Zhao ◽  
Xiaodong Liu ◽  
Kai Zhang
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Unscented Kalman Filter ◽  
Stability Control ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
The Road ◽  
Experiment Platform ◽  
Ant Lion Optimization ◽  
Ant Lion

Accurate estimation of vehicle states is extremely crucial for vehicle stability control. As a reliable estimation methodology, the unscented Kalman filter (UKF) has been widely utilized in vehicle control. However, the estimation accuracy still needs to be improved caused by the unpredictable measurement and process noise. In this paper, a novel modified UKF state estimation methodology combined with the ant lion optimization (ALO) is proposed for the stability control of a four in-wheel motor independent drive electric vehicle (4WIDEV). First, the optimal performance of the ALO algorithm is analyzed, where both unimodal and multimodal optimization test functions are selected and optimized by GA, PSO, and ALO, respectively. The results indicate that the ALO algorithm has good global optimization capability and applicability. Second, the ALO algorithm is merged into the UKF to adjust the statistical properties of noise information for the ALOUKF estimator design without extra sensor signals. At last, the simulations on the Matlab/Simulink-CarSim co-simulation platform and the road test based on an A&D 5435 rapid prototyping experiment platform (RPP) are carried out to verify the proposed method. The simulation and experiment results demonstrate that the ALOUKF estimator can improve state estimation accuracy and resist the vehicle nonlinearity even in the case of the complicated and emergency maneuvers.

scholarly journals Road Tracking from High resolution IRS And IKONOS Images Using Unscented Kalman Filtering

2011 ◽  
pp. 5-11
Author(s):  
Jenita Subash ◽  
Madhan Kumar K
Keyword(s):  
Kalman Filter ◽  
Satellite Images ◽  
Unscented Kalman Filter ◽  
Image Interpretation ◽  
Estimation Algorithm ◽  
The Road ◽  
Median Axis ◽  
Interpretation System ◽  
Road Maps ◽  
Map Data

A typical way to update map is to compare recent satellite images with existing map data, detect new roads and add them as cartographic entities to the road layer. At present image processing and pattern recognition are not robust enough to automate the image interpretation system feasible. For this reason we have to develop an image interpretation system that rely on human guidance. More importantly road maps require final checking by a human due to the legal implementations of error. Our proposed technique is applied to IRS and IKONOS images using Unscented Kalman Filter(UKF) . UKF is used for tracing the median axis of the single road segment. The Extended Kalman Filter (EKF) is probably the most widely used estimation algorithm for road tracking. However, more than 35 years of experience in the estimation community has shown that is difficult to implement and is difficult to tune. To overcome this limitation,UKF is introduced in road tracking which is more accurate, easier to implement, and uses the same order of calculations as linearization. The principles and algorithm of EKF and UKF were also discussed. The core of our system is based on profile matching.UKF traces the roadbeyond obstacles and tries to find the continuation of the road finding all road branches initializing at the road junction.The completeness and correctness of road tracking from the IRS and IKONOS images were also compared.

scholarly journals A Methodology to Investigate Powered Two-Wheeler Rider’s Comfort over Road Sections with Skew Superelevation

2021 ◽  
Vol 16 ◽  
pp. 592-599
Author(s):  
Panagiotis Lemonakis ◽  
George Kaliabetsos ◽  
Nikolaos Moisiadis ◽  
Nikolaos Eliou
Keyword(s):  
Traffic Safety ◽  
Vertical Acceleration ◽  
Water Drainage ◽  
Safety Level ◽  
Important Conclusion ◽  
The Road ◽  
Car Suspension ◽  
Longitudinal Slope ◽  
Suspension Model ◽  
Two Wheeler

The proper surface water drainage not only affects vehicle movement dynamics but also increases the likelihood of an accident since inadequate drainage is associated with potential hydroplaning and splash and spray driving conditions. Nine solutions have been proposed to address hydroplaning in sections with inadequate drainage e.g. augmented superelevation and longitudinal slope, reduction of runoff length, and skew superelevation. The latter has been extensively implemented in highways recently, enhancing the safety level in the applied road segments regarding the effective drainage of the rainwater. However, the concept of the skew superelevation has raised concerns regarding the level of driver’s comfort when traveling over skew superelevation sections particularly with high speeds. These concerns were alleviated through the concept of the round-up skew superelevation which reduces both the lateral and the vertical acceleration imposed on the drivers and hence, improves comfort and traffic safety. The present study investigates the behaviour of power two-wheeler riders since they are susceptible to any changes on the pavement surface and therefore a comparison between the traditional superelevation practice and the skew superelevation concept is of paramount importance. The methodology is based on the utilization of sophisticated software to design the model of the road for several values of longitudinal slopes. Based on the values of the slopes and the use of mathematical equations, the accelerations imposed on the wheel of the motorcycle were calculated. Since the final aim of the study is the influence of the skew superelevation to the rider, it was deemed necessary to convey the calculated accelerations from the wheel to the rider. That was accomplished by implementing the quarter car suspension model adjusted to the features of two-wheeler vehicles. Finally, the accelerations derived from this process evaluated according to specific thresholds based on the literature which correspond to certain levels of comfort. The most important conclusion drawn is that the comfort of the riders is not dependent to a great extent on the form of the road gradient because the vertical acceleration imposed on the riders took similar values regardless of the value of the longitudinal slope.

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