Tire-Road Friction Coefficient Estimation and Experimental Setup Design of Electric Vehicle

Elmas, Çetin; Güvenç, Uğur; Doğan, Muhsin Uğur

doi:10.17694/bajece.88174

Cited by 4 publications

(5 citation statements)

References 8 publications

(9 reference statements)

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“…For calculation of friction force of the wheel or tire transferred to the road, Burckhardt's tire modeling has been adapted. This model has been widely used due to its better accuracy in the explanation of friction coefficient [4,17]. The equation governing this tire model is given by:…”

Section: Tire Modelingmentioning

confidence: 99%

Design and Analysis of Vehicle Anti-Lock Braking System with Fuzzy Logic, Bang-Bang and PID Controllers

Lakhemaru

Adhikari

2022

Himalayan J. Appl. Sci. Engin.

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In this study, a mathematical model of Anti-Lock Braking System (ABS) has been developed and simulated in MATLAB/Simulink environment using bang-bang, fuzzy logic and PID controllers. The controllers were used to control the braking force to be applied based on various parameters like relative slip, road condition and coefficient of friction between road and tire. The simulated result was compared and analyzed. The simulation result showed that a PID controller would take 9.665 seconds to stop the vehicle at the distance of 434.902 ft at an initial velocity of 88 ft/s. The Fuzzy Logic, Bang-Bang and no controllers offered 935.298 ft at 16.76 seconds, 696.996 ft at 13.751 seconds and 1421.327 ft at 24.217 seconds, respectively for the same initial velocity and road surface. From analysis, it was concluded that the PID controller had better performance compared to fuzzy logic and bang-bang controllers for application of ABS in a vehicle.

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Section: Tire Modelingmentioning

confidence: 99%

Design and Analysis of Vehicle Anti-Lock Braking System with Fuzzy Logic, Bang-Bang and PID Controllers

Lakhemaru

Adhikari

2022

Himalayan J. Appl. Sci. Engin.

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“…where denotes the volume of pack i. This integer linear programming problem needs to be solved with the objective function equation (10) and restrictions equation 2, equation (8) for all , ∈ , < . In order to solve this problem first fit decreasing (FFD) algorithm is used [39]- [41].…”

Section: B Optimal Bin Packingmentioning

confidence: 99%

“…The technology behind the trolleybus systems has not changed drastically since those days [7]. If one looks at today's modern trolleybuses can see that AC motors with inverters took place of DC motors, metal wheels changed to regular bus tires; this let trolleybuses navigate through regular roads instead of railways [8], [9]. Therefore, trolleybuses became more like buses, rather than trains.…”

Section: Introductionmentioning

confidence: 99%

Electrification in Urban Transport: A Case Study with Real-time Data

Dikmen

Ekici

Karadağ

et al. 2021

Balkan Journal of Electrical and Computer Engineering

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Electrification in urban transportation is becoming more popular, it is also becoming a necessity due to climate changes and sustainability issues. Trolleybuses are presenting an alternative for this purpose. Although their technology is a mature technology that has been used for decades, there are still some technical problems that need to be overcome. In this study, a technical method is presented for the conversion of trolleybus auxiliary power units. The electrification conversion demanded by the metropolitan public transportation company operating 22 trolleybuses in the province of Malatya is the replacement of diesel generators, used as auxiliary power units, with battery units capable of meeting the local operational requirements. For this purpose, a method is proposed and followed. At the first step of the implementation, real-time data has gathered from a trolleybus and this one round tour data is used to run on a scaled experiment. The setup has prepared as hardware and software to simulate the consumption on a scaled battery pack. Experimental results were interpreted with capacity and voltage restrictions resulting in the determination of battery chemistry and casing to be used. Then optimal battery placement was defined as a container loading problem and application was made with the first fit decreasing algorithm considering mass and volume restrictions. It was found that only two packing types out of six combinations are enough to form a battery pack within the mass and volumetric limitations. It is evaluated that the method İSMAİL CAN DİKMEN, is with

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“…When the adhesion coefficients of different rail surfaces are estimated, the practical slip ratio can be controlled to reach the optimal slip ratio corresponding to the peak value of adhesion coefficients. In general, two methods are used to obtain real‐time optimal slip ratio: a model‐based method [4] and a method based on the online estimation of extreme values [5]. The model‐based method identifies the parameters in the model online according to classic models of adhesion characteristic curves, such as least square estimation [6] and maximum likelihood estimator [7], to find the extremum in mathematical models and obtain the optimal slip ratio.…”

Section: Introductionmentioning

confidence: 99%