Effect of Load-Dependent Friction on the Estimation of Rack Force in Electric Power-Assisted Steering System

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Yijun Li ◽  
Taehyun Shim ◽  
Dexin Wang ◽  
Timothy Offerle
Keyword(s):  
Electric Power ◽  
A Priori ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Steering System ◽  
Estimation Methods ◽  
Current Steering ◽  
Force Estimation ◽  
Operation Conditions ◽  
Friction Estimation

The rack force is valuable information for a vehicle dynamics control system, as it relates closely to the road conditions and steering feel. Since there is no direct measurement of rack force in current steering systems, various rack force estimation methods have been proposed to obtain the rack force information. In order to get an accurate rack force estimate, it is important to have knowledge of the steering system friction. However, it is hard to have an accurate value of friction, as it is subject to variation due to operation conditions and material wear. Especially for the widely used column-assisted electric power steering (C-EPAS) system, the load-dependent characteristic of its worm gear friction has a significant effect on rack force estimation. In this paper, a rack force estimation method using a Kalman filter and a load-dependent friction estimation algorithm is introduced, and the effect of C-EPAS friction on rack force estimator performance is investigated. Unlike other rack force estimation methods, which assume that friction is known a priori, the proposed system uses a load-dependent friction estimation algorithm to determine accurate friction information in the steering system, and then a rack force is estimated using the relationship between steering torque and angle. The effectiveness of this proposed method is verified by carsim/simulink cosimulation.

Comparative Study of Rack Force Estimation for Electric Power Assist Steering System

2017 ◽  
Author(s):  
Yijun Li ◽  
Taehyun Shim ◽  
Dexin Wang ◽  
Timothy Offerle
Keyword(s):  
Control System ◽  
Electric Power ◽  
Vehicle Dynamics ◽  
System Development ◽  
Steering System ◽  
Estimation Methods ◽  
Simulation Environment ◽  
Force Estimation ◽  
Adaptation Algorithm ◽  
Estimation Algorithms

For an electric power assist steering (EPAS) control system, it is important to know the rack force information to improve the steering feel control performance. Since there is no direct measurement of rack force in current EPAS system, there have been various rack force estimation algorithms proposed for the control system development. In this paper, two existing rack force estimation methods (based on steering system dynamics and vehicle dynamics) have been implemented in the simulation environment to compare its performance. The effectiveness and limitations of two methods have been analyzed using a simulation of high fidelity EPAS model with various inputs conditions. In addition, new adaptation algorithm is proposed to further improve the estimation performance of the existing methods.

scholarly journals A Fast and Accurate Guessing Entropy Estimation Algorithm for Full-key Recovery

2020 ◽  
pp. 26-48
Author(s):  
Ziyue Zhang ◽  
A. Adam Ding ◽  
Yunsi Fei
Keyword(s):  
Experimental Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Security Evaluation ◽  
Side Channel ◽  
Data Sets ◽  
Key Recovery ◽  
Entropy Estimation

Guessing entropy (GE) is a widely adopted metric that measures the average computational cost needed for a successful side-channel analysis (SCA). However, with current estimation methods where the evaluator has to average the correct key rank over many independent side-channel leakage measurement sets, full-key GE estimation is impractical due to its prohibitive computing requirement. A recent estimation method based on posterior probabilities, although scalable, is not accurate.We propose a new guessing entropy estimation algorithm (GEEA) based on theoretical distributions of the ranking score vectors. By discovering the relationship of GE with pairwise success rates and utilizing it, GEEA uses a sum of many univariate Gaussian probabilities instead of multi-variate Gaussian probabilities, significantly improving the computation efficiency.We show that GEEA is more accurate and efficient than all current GE estimations. To the best of our knowledge, it is the only practical full-key GE evaluation on given experimental data sets which the evaluator has access to. Moreover, it can accurately predict the GE for larger sizes than the experimental data sets, providing comprehensive security evaluation.

Rack Force Estimation for Electric Power Steering

2015 ◽  
Author(s):  
Thomas Weiskircher ◽  
Steve Fankem ◽  
Beshah Ayalew
Keyword(s):  
Electric Power ◽  
Steering System ◽  
Force Estimation ◽  
Test Rig ◽  
Electric Power Steering ◽  
Power Steering ◽  
Electric Power Steering System ◽  
Estimation Scheme ◽  
Friction Identification ◽  
Linear Disturbance

This paper discusses a steering rack force estimation scheme using test-rig generated models. In addition to friction identification, a model of the electric power steering system is identified by the use of the instrumented test-rig. It turns out that the friction in the steering system is highly load-dependent, asymmetric with respect to speed, and shows no Stribeck effects. A LuGre model is adopted and fitted to approximate the measured dynamic friction. Consequently, this model is used in a friction compensator which is combined with a linear disturbance observer to estimate the steering rack force. The proposed estimation scheme is analyzed via evaluated system simulations and experiments on the steering system test-rig. Finally, considering the fact that the friction level varies with each steering device manufactured and installed, the paper discusses algorithms for friction level adaptation.

A Review of Research on the State-of-Charge Estimation Methods for Electric Vehicle Battery

2019 ◽  
Vol 13 ◽  
Author(s):  
Mingyue Zhang ◽  
Xiaobin Fan ◽  
Jing Gan ◽  
Zeng Song ◽  
Bin Zhao
Keyword(s):  
Control Theory ◽  
Electric Vehicle ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
The State ◽  
State Of Charge ◽  
Estimation Methods ◽  
Advantages And Disadvantages ◽  
Electric Vehicle Battery ◽  
State Of Charge Estimation

Background: Battery technology has been one of the bottlenecks in electric cars. Whether it is in theory or in practice, the research on battery management is extremely important, especially for battery state-of-charge estimation. In fact, the battery has a strong time change and non-linear properties, which are extremely complex systems. Therefore, accurate estimating the state of charge is a challenging thing. Objective: The study aims to report the latest progress in the studies of the state-of-charge estimation methods for electric vehicle battery. Methods: This paper reviews various representative patents and papers related to the state of charge estimation methods for electric vehicle battery. According to their theoretical and experimental characteristics, the estimation methods were classified into three groups: the traditional estimation algorithm based on the battery experiment, the estimation algorithm based on modern control theory and other estimation algorithm based on the innovative ideas, especially focusing on the algorithms based on control theory. Results: The advantages and disadvantages, current and future developments of the state-of-charge estimation methods are finally provided and discussed. Conclusion: Each kind of state of charge estimation method has its own characteristics, suitable for different occasions. At present, algorithms based on control theory, especially intelligent algorithms, are the focus of research in this field. The future development direction is to establish rich database, improve hardware technology, put up with more perfect battery model, and give full play to the advantages of each algorithm.

scholarly journals Adaptive Nonlinear Tire-Road Friction Force Estimation for Vehicular Systems Based on a Novel Differentiable Friction Model

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Wei-Dong Xie ◽  
Xiao-Bin Ning
Keyword(s):  
Friction Force ◽  
Estimation Algorithm ◽  
Friction Model ◽  
Lyapunov Theory ◽  
Nonlinear Observer ◽  
Estimation Methods ◽  
Vehicle Speed ◽  
Force Estimation ◽  
Observer Error ◽  
Road Friction

A novel adaptive nonlinear observer-based parameter estimation scheme using a newly continuously differentiable friction model has been developed to estimate the tire-road friction force. The differentiable friction model is more flexible and suitable for online adaptive identification and control with the advantage of more explicit parameterizable form. Different from conventional estimation methods, the filtered regression estimation parameter is introduced in the novel adaptive laws, which can guarantee that both the observer error and parameter error exponentially converge to zero. Lyapunov theory has been used to prove the stability of the proposed methods. The effectiveness of the estimation algorithm is illustrated via a bus simulation model in the Trucksim software and simulation environment. The relatively accurate tire-road friction force was estimated just by the easily existing sensors signals wheel rotational speed and vehicle speed and the proposed method also displays strong robustness against bounded disturbances.

scholarly journals Estimators for Time Synchronization—Survey, Analysis, and Outlook

IoT ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 398-435
Author(s):  
Henning Puttnies ◽  
Peter Danielis ◽  
Ali Rehan Sharif ◽  
Dirk Timmermann
Keyword(s):  
Time Synchronization ◽  
Clock Synchronization ◽  
Distributed Databases ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Research Area ◽  
Estimation Methods ◽  
Survey Analysis ◽  
Experimental Conditions ◽  
Survey Paper

Time (or clock) synchronization is a large and vital field of research, as synchronization is a precondition for many applications. A few example applications are distributed data acquisition, distributed databases, and real-time communication. First, this survey paper introduces the research area of time synchronization and emphasizes its relation to other research areas. Second, we give an overview of the state-of-the-art of time synchronization. Herein, we discuss both established protocol and research approaches. We analyze all techniques according to three criteria: used estimation algorithm, achievable synchronization accuracy, and the experimental conditions. In our opinion, this analysis highlights potential improvements. The most important question in this survey is as follows: which estimation method can be used to achieve which accuracies under which conditions? The intention behind this is to identify estimation methods that are particularly worth considering, as these already achieve good results in the wireless area but have not yet been examined in the wired area (and vice versa). This survey paper differs from other surveys in particular through the consideration of wireless and wired synchronization and the focus on estimation algorithms and their achievable accuracy.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

Web-based Tools for Drug Repurposing: Successful Examples of Collaborative Research

2020 ◽  
Vol 28 (1) ◽  
pp. 181-195
Author(s):  
Quentin Vanhaelen
Keyword(s):  
User Interfaces ◽  
Collaborative Research ◽  
Meta Analysis ◽  
A Priori ◽  
Drug Repurposing ◽  
Data Access ◽  
Estimation Methods ◽  
Large Set ◽  
Computational Tools ◽  
Web Based

: Computational approaches have been proven to be complementary tools of interest in identifying potential candidates for drug repurposing. However, although the methods developed so far offer interesting opportunities and could contribute to solving issues faced by the pharmaceutical sector, they also come with their constraints. Indeed, specific challenges ranging from data access, standardization and integration to the implementation of reliable and coherent validation methods must be addressed to allow systematic use at a larger scale. In this mini-review, we cover computational tools recently developed for addressing some of these challenges. This includes specific databases providing accessibility to a large set of curated data with standardized annotations, web-based tools integrating flexible user interfaces to perform fast computational repurposing experiments and standardized datasets specifically annotated and balanced for validating new computational drug repurposing methods. Interestingly, these new databases combined with the increasing number of information about the outcomes of drug repurposing studies can be used to perform a meta-analysis to identify key properties associated with successful drug repurposing cases. This information could further be used to design estimation methods to compute a priori assessment of the repurposing possibilities.

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