Development of enhanced ESP system through vehicle parameter estimation

Lee, Hansung; Park, Kihong; Hwang, Taehun; Noh, Keunje; Heo, Seung-Jin; Jeong, Jin-Yeon; Choi, Seongho; Kwak, Byung Man; Kim, Sewoong

doi:10.1007/s12206-009-0338-z

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…e rut water depth and the 3D tire-road finite element model are used to calculate the adhesion coefficient between the tire and the water-accumulated road surface. Based on the dynamic differential equation theory and the vehicle model (fourwheel model) [16][17][18], a 3D water-filled rut-adhesion coefficient-vehicle model with 27 degrees of freedom is stabled and used for driving safety analysis. As shown in Figure 8, the left front wheel is taken as an example to describe the dynamic differential equation of the vehicle motion.…”

Section: Establishment Of 3d Water-accumulated Rut-adhesion Coefficient-vehicle Model and Safety Analysismentioning

confidence: 99%

“…It can import road information (including road alignment, vertical elevation of cross section, and adhesion coefficient) and vehicle parameter information through different modules. In the car simulator, the mathematical model of the vehicle four-wheel model has over 110 ordinary differential equations and 250 state variables that can fully define the state of the system [16][17][18]. In addition, many researchers, including Cao et al [20], Guo [14], Zhang [15], and Pilgrim [21], also use CarSim to simulate and analyze the safety problems arising from the reduced adhesion coefficient between the road surface and the vehicle.…”

Section: Establishment Of 3d Water-accumulated Rut-adhesion Coefficient-vehicle Model and Safety Analysismentioning

confidence: 99%

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Driving Safety Analysis Using Grid‐Based Water‐Filled Rut Depth Distribution

Yan

Zhang²,

Hui

2021

Advances in Materials Science and Engineering

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The water accumulated in the rutted road sections poses a threat to the safety of vehicles. Water-filled ruts will cause partial or complete loss of the friction between tires and the road surface, leading to driving safety hazards such as hydroplaning and sliding. At present, the maximum water depth of left and right ruts is mostly adopted to analyze the safety of water-filled ruts, ignoring the uneven change of ruts in the driving direction and the cross-section direction, which cannot fully reflect the actual impact of asymmetric or uneven longitudinal ruts on the vehicle. In order to explore the impact of water-filled ruts on driving safety, a three-dimensional (3D) tire-road finite element model is established in this paper to calculate the adhesion coefficient between the tire and the road surface. Moreover, a model of the 3D water-filled rut-adhesion coefficient vehicle is established and simulated by the dynamics software CarSim. In addition, the influence of the water depth difference between the left and right ruts on the driving safety is quantitatively analyzed, and a safety prediction model for the water-filled rut is established. The results of the case study show that (1) the length of dangerous road sections based on vehicle skidding is longer than that based on hydroplaning, and the length of dangerous road sections based on hydroplaning is underestimated by 9.4%–100%; (2) as the vehicle speed drops from 120 km/h to 80 km/h, the length of dangerous road sections obtained based on vehicle sliding analysis is reduced by 93.8%. Therefore, in order to ensure driving safety, the speed limit is controlled within 80 km/h to ensure that the vehicle will not skid. The proposed method provides a good foundation for the vehicles to actively respond to the situation of the water-filled road section.

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Section: Establishment Of 3d Water-accumulated Rut-adhesion Coefficient-vehicle Model and Safety Analysismentioning

confidence: 99%

Section: Establishment Of 3d Water-accumulated Rut-adhesion Coefficient-vehicle Model and Safety Analysismentioning

confidence: 99%

Driving Safety Analysis Using Grid‐Based Water‐Filled Rut Depth Distribution

Yan

Zhang²,

Hui

2021

Advances in Materials Science and Engineering

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“…This methodology is suitable for current ESP systems, as a yaw rate error controller limits the maximum departures from the ''desired'' yaw rate calculated using the characteristic speed. 17 This traditional approach to vehicle safety is based on the controllability concept discussed in. 18 The author retakes the beta-method (portrait of the yaw moment versus the body slip for different steering angles), first introduced in Shibahata et al, 19 and uses it to explain the reduction in the vehicle controllability (available yaw moment) with the increase in the body slip angle.…”

Section: Motivationmentioning

confidence: 99%

Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques

Acosta

Kanarachos

Blundell

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a comprehensive literature review on tyre force estimation and road grip recognition approaches. With the development of modern automotive control systems, a precise estimation of a large number of vehicle states is necessary to guarantee a robust actuation of the controller. Moreover, the estimation of these states must be carried out in a cost-effective and reliable way. The aim of this work is to provide a solid base for the development of automotive virtual sensors, and in particular, virtual tyre force sensors. An initial overview of the tyre force estimation problem is provided in the first section. Tyre and vehicle modelling, as well as observers for vehicle state estimation, are covered in detail in the second section. The third section introduces a brief discussion regarding the main limitations of direct tyre force measurement approaches. In the following sections, relevant works regarding three-axis tyre force estimation and road grip recognition are discussed. The review is structured around longitudinal force estimation, lateral force estimation, combined tyre force estimation, tyre self-alignment torque estimation and vertical tyre force estimation. Within each section, the most significant road grip identification approaches are introduced. An additional section, Road slope and bank angle compensation, describes relevant work on estimation methods for global chassis orientation. A brief summary of the presented approaches is provided in the section Summary of presented approaches. Finally, relevant conclusions and further research steps are given in the last section.

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