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    ๊ณ ์„ฑ๋Šฅ ํ•œ๊ณ„ ํ•ธ๋“ค๋ง์„ ์œ„ํ•œ ์ธํœ ๋ชจํ„ฐ ํ† ํฌ๋ฒกํ„ฐ๋ง ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2021.8. ์ด๊ฒฝ์ˆ˜.์ง€๋‚œ 10๋…„ ๋™์•ˆ ์ฐจ๋Ÿ‰ ์ž์„ธ ์ œ์–ด์‹œ์Šคํ…œ(ESC)์€ ์น˜๋ช…์ ์ธ ์ถฉ๋Œ์„ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ๋งŽ์€ ์ƒ์šฉ ์ฐจ๋Ÿ‰์—์„œ ๋น„์•ฝ์ ์œผ๋กœ ๋ฐœ์ „๋˜๊ณ  ๊ฐœ๋ฐœ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ์ฐจ๋Ÿ‰ ์ž์„ธ ์ œ์–ด ์‹œ์Šคํ…œ์€ ์•…์ฒœํ›„๋กœ ์ธํ•œ ๋ฏธ๋„๋Ÿฌ์šด ๋„๋กœ์™€ ๊ฐ™์€ ์œ„ํ—˜ํ•œ ๋„๋กœ์—์„œ ๋ถˆ์•ˆ์ •ํ•œ ์ฐจ๋Ÿ‰ ์ฃผํ–‰ ์กฐ๊ฑด์—์„œ ์‚ฌ๊ณ ๋ฅผ ํ”ผํ•˜๋Š”๋ฐ ํฐ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ตœ๊ทผ์˜ ๊ฒฝ์šฐ, ๊ณ ์„ฑ๋Šฅ ์ฐจ๋Ÿ‰ ๋˜๋Š” ์Šคํฌ์ธ ์นด ๋“ฑ์˜ ๊ฒฝ์šฐ ์ œ๋™์ œ์–ด์˜ ๋นˆ๋ฒˆํ•œ ๊ฐœ์ž…์€ ์šด์ „์˜ ์ฆ๊ฑฐ์›€์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ๋ถˆ๋งŒ๋„ ์กด์žฌํ•œ๋‹ค. ์ตœ๊ทผ ์ฐจ๋Ÿ‰์˜ ์ „๋™ํ™”์™€ ํ•จ๊ป˜, ์ž๋Ÿ‰ ์ž์„ธ ์ œ์–ด์‹œ์Šคํ…œ์˜ ์ž‘๋™ ์˜์—ญ์ธ ํ•œ๊ณ„ ์ฃผํ–‰ ํ•ธ๋“ค๋ง ์กฐ๊ฑด์—์„œ ๊ฐ ํœ ์˜ ๋…๋ฆฝ์ ์ธ ๊ตฌ๋™์„ ์ ์šฉ ํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ ์ค‘ ํ•˜๋‚˜์ธ ์ธํœ  ๋ชจํ„ฐ ์‹œ์Šคํ…œ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ฐจ๋Ÿ‰์˜ ์ข…, ํšก๋ฐฉํ–ฅ ํŠน์„ฑ์„ ์ œ์–ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ํ† ํฌ ๋ฒกํ„ฐ๋ง ์ œ์–ด๊ธฐ์ˆ ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ฐจ๋Ÿ‰์˜ ์„ ํšŒ ํ•œ๊ณ„ ํ•ธ๋“ค๋ง ์กฐ๊ฑด์—์„œ ์•ˆ์ •์„ฑ๊ณผ ์ฃผํ–‰ ๋‹ค์ด๋‚˜๋ฏน ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ํ† ํฌ ๋ฒกํ„ฐ๋ง ์ œ์–ด๊ธฐ๋ฅผ ์ œ์•ˆํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋จผ์ €, ์ฐจ๋Ÿ‰์˜ ๋น„์„ ํ˜• ์ฃผํ–‰ ๊ตฌ๊ฐ„์ธ ํ•œ๊ณ„ ํ•ธ๋“ค๋ง ์กฐ๊ฑด์— ๋Œ€ํ•œ ์ž๋™ ๋“œ๋ฆฌํ”„ํŠธ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜์—ฌ ํ† ํฌ๋ฒกํ„ฐ๋ง์ œ์–ด์— ์ฐจ๋Ÿ‰์˜ ๋‹ค์ด๋‚˜๋ฏนํ•œ ์ฃผํ–‰๋ชจ๋“œ์— ๋Œ€ํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•˜๊ณ  ๋ฏธ๋„๋Ÿฌ์šด ๋„๋กœ์—์„œ ์ฐจ๋Ÿ‰์˜ ๋†’์€ ์Šฌ๋ฆฝ ๊ฐ๋„์˜ ์•ˆ์ •์„ฑ ์ œ์–ด๋ฅผ ์ œ๊ณต ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ธํœ  ๋ชจํ„ฐ ์‹œ์Šคํ…œ์„ ์ฐจ๋Ÿ‰์˜ ์ „๋ฅœ์— 2๊ฐœ ๋ชจํ„ฐ๋กœ ์‚ฌ์šฉํ•˜์—ฌ ์ฐจ๋Ÿ‰ ๊ณ ์œ ์˜ ํŠน์„ฑ์ธ ์ฐจ๋Ÿ‰ ์–ธ๋”์Šคํ‹ฐ์–ด ๊ตฌ๋ฐฐ๋ฅผ ์ง์ ‘์  ์ œ์–ด๋ฅผ ์ˆ˜ํ–‰ํ•˜์—ฌ, ์ฐจ๋Ÿ‰์˜ ํ•ธ๋“ค๋ง ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œ์ผฐ๋‹ค. ์ œ์–ด๊ธฐ์˜ ์ฑ„ํ„ฐ๋ง ํšจ๊ณผ๋ฅผ ์ค„์ด๊ณ  ๋น ๋ฅธ ์‘๋‹ต์„ ์–ป๊ธฐ ์œ„ํ•ด ์ƒˆ๋กœ์šด ๊ณผ๋„ ๋งค๊ฐœ ๋ณ€์ˆ˜๊ฐ€ ์ด์šฉํ•˜์—ฌ ์ˆ˜์‹ํ™”ํ•˜์—ฌ ๊ตฌ์„ฑํ•˜์˜€์œผ๋ฉฐ, ์ฐจ๋Ÿ‰์˜ ์ •์ƒ ์ƒํƒœ ๋ฐ ๊ณผ๋„ ํŠน์„ฑ ํ–ฅ์ƒ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ISO ๊ธฐ๋ฐ˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ์ฐจ๋Ÿ‰ ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์š” ์ œ์–ด๊ธฐ์™€ ํšก ์Šฌ๋ฆฝ ๊ฐ๋„ ์ œ์–ด๊ธฐ๋กœ ๊ตฌ์„ฑ๋œ MASMC (Multiple Adaptive Sliding Mode Control) ์ ‘๊ทผ ๋ฐฉ์‹์„ ์‚ฌ์šฉํ•˜๋Š” 4๋ฅœ ๋ชจํ„ฐ ์‹œ์Šคํ…œ์„ ์‚ฌ์šฉํ•œ ๋™์  ํ† ํฌ๋ฒกํ„ฐ๋ง ์ œ์–ด๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋†’์€ ๋น„์„ ํ˜• ํŠน์„ฑ์„ ๊ฐ€์ง„ ์ฐจ๋Ÿ‰์˜ ์ „ํ›„๋ฅœ ํƒ€์ด์–ด์˜ ์ฝ”๋„ˆ๋ง ๊ฐ•์„ฑ์€ ์ ์‘์ œ์–ด๊ธฐ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์˜ˆ์ธกํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ, ์•ˆ์ „๋ชจ๋“œ์™€ ๋‹ค์ด๋‚˜๋ฏน ๋ชจ๋“œ๋ฅผ ๊ตฌ์„ฑํ•˜์—ฌ, ์šด์ „์ž๋กœ ํ•˜์—ฌ๊ธˆ ์›ํ•˜๋Š” ์ฃผํ–‰์˜ ์กฐ๊ฑด์— ๋งž๊ฒŒ ์„ ํƒํ•  ์ˆ˜ ์žˆ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ์ด MASMC ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ํ–ฅํ›„ ์ „๋™ํ™” ์ฐจ๋Ÿ‰์— ์ฃผํ–‰์•ˆ์ •์„ฑ ํ–ฅ์ƒ๊ณผ ๋‹ค์ด๋‚˜๋ฏนํ•œ ์ฃผํ–‰์˜ ์ฆ๊ฑฐ์›€์„ ์ฃผ๋Š” ๊ธฐ์ˆ ๋กœ์จ, ์ „์ฐจ๋Ÿ‰ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ด์šฉํ•˜์—ฌ ๊ฒ€์ฆํ•˜์˜€๋‹ค.In the last ten decades, vehicle stability control systems have been dramatically developed and adapted in many commercial vehicles to avoid fatal crashes. Significantly, ESC (Electric Stability Control) system can help escape the accident from unstable driving conditions with dangerous roads such as slippery roads due to inclement weather conditions. However, for the high performed vehicle, frequent intervention from ESC reduces the pleasure of fun-to-drive. Recently, the development of traction control technologies has been taking place with that of the electrification of vehicles. The IWMs (In-Wheel Motor system), which is one of the systems that can apply independent drive of each wheel, for the limit handling characteristics, which are the operation areas of the ESC, is introduced for the control that enables the lateral characteristics of the vehicle dynamics. Firstly, the automated drift control algorithm can be proposed for the nonlinear limit handling condition of vehicles. This approach can give an insight of fun-to-drive mode to TV (Torque Vector) control scheme, but also the stability control of high sideslip angle of the vehicle on slippery roads. Secondly, using IWMs system with front two motors, understeer gradient of vehicle, which is the unique characteristics of vehicle can be used for the proposed control strategy. A new transient parameter is formulated to be acquired rapid response of controller and reducing chattering effects. Simulation and vehicle tests are conducted for validation of TV control algorithm with steady-state and transient ISO-based tests. Finally, dynamic torque vectoring control with a four-wheel motor system with Multiple Adaptive Sliding Mode Control (MASMC) approach, which is composed of a yaw rate controller and sideslip angle controller, is introduced. Highly nonlinear characteristics, cornering stiffnesses of front and rear tires are estimated by adaptation law with measuring data. Consequently, there are two types of driving modes, the safety mode and the dynamic mode. MASMC algorithm can be found and validated by simulation in torque vectoring technology to improve the handling performance of fully electric vehicles.Chapter 1 Introduction 7 1.1. Background and Motivation 7 1.2. Literature review 11 1.3. Thesis Objectives 15 1.4. Thesis Outline 15 Chapter 2 Vehicle dynamic control at limit handling 17 2.1. Vehicle Model and Analysis 17 2.1.1. Lateral dynamics of vehicle 17 2.1.2. Longitudinal dynamics of vehicle 20 2.2. Tire Model 24 2.3. Analysis of vehicle drift for fun-to-drive 28 2.4. Designing A Controller for Automated Drift 34 2.4.1. Lateral controller 35 2.4.2. Longitudinal Controller 37 2.4.3. Stability Analysis 39 2.4.4. Validation with simulation and test 40 Chapter 3 Torque Vectoring Control with Front Two Motor In-Wheel Vehicles 47 3.1. Dynamic Torque Vectoring Control 48 3.1.1. In-wheel motor system (IWMs) 48 3.1.2. Dynamic system modeling 49 3.1.3. Designing controller 53 3.2. Validation with Simulation and Experiment 59 3.2.1. Simulation 59 3.2.2. Vehicle Experiment 64 Chapter 4 Dynamic handling control for Four-wheel Drive In-Wheel platform 75 4.1. Vehicle System Modeling 76 4.2. Motion Control based on MASMC 78 4.2.1. Yaw motion controller for the inner ASMC 80 4.2.2. Sideslip angle controller for the outer ASMC 84 4.3. Optimal Torque Distribution (OTD) 88 4.3.1. Constraints of dynamics 88 4.3.2. Optimal torque distribution law 90 4.4. Validation with Simulation 91 4.4.1. Simulation setup 91 4.4.2. Simulation results 92 Chapter 5 Conclusion and Future works 104 5.1 Conclusion 104 5.2 Future works 106 Bibliography 108 Abstract in Korean 114๋ฐ•

    A Multi-Motor Architecture for Electric Vehicles

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    This paper proposes an architecture for EVs with three or more electric motors and highlights when adding more motors does not impact the battery state of charge (SOC). The proposed control algorithm optimizes the use of the motors onboard to keep them running in their most efficient regions. Simulation results along with a comparison with other current motors used in EVs is presented in this paper, and further discussion on the results is presented. With this architecture, the powertrain would see a combined efficiency map that incorporates the best operating points of the motors. Therefore, the proposed architecture will allow the EV to operate with a higher range for a given battery capacity

    Torque vectoring based drive assistance system for turning an electric narrow tilting vehicle

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    The increasing number of cars leads to traffic congestion and limits parking issue in urban area. The narrow tilting vehicles therefore can potentially become the next generation of city cars due to its narrow width. However, due to the difficulty in leaning a narrow tilting vehicle, a drive assistance strategy is required to maintain its roll stability during a turn. This article presents an effective approach using torque vectoring method to assist the rider in balancing the narrow tilting vehicles, thus reducing the counter-steering requirements. The proposed approach is designed as the combination of two torque controllers: steer angleโ€“based torque vectoring controller and tilting compensatorโ€“based torque vectoring controller. The steer angleโ€“based torque vectoring controller reduces the counter-steering process via adjusting the vectoring torque based on the steering angle from the rider. Meanwhile, the tilting compensatorโ€“based torque vectoring controller develops the steer angleโ€“based torque vectoring with an additional tilting compensator to help balancing the leaning behaviour of narrow tilting vehicles. Numerical simulations with a number of case studies have been carried out to verify the performance of designed controllers. The results imply that the counter-steering process can be eliminated and the roll stability performance can be improved with the usage of the presented approach

    Application of Fuzzy control algorithms for electric vehicle antilock braking/traction control systems

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    Abstractโ€”The application of fuzzy-based control strategies has recently gained enormous recognition as an approach for the rapid development of effective controllers for nonlinear time-variant systems. This paper describes the preliminary research and implementation of a fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking systems (ABSs). As the dynamics of the braking systems are highly nonlinear and time variant, fuzzy control offers potential as an important tool for development of robust traction control. Simulation studies are employed to derive an initial rule base that is then tested on an experimental test facility representing the dynamics of a braking system. The test facility is composed of an induction machine load operating in the generating region. It is shown that the torque-slip characteristics of an induction motor provides a convenient platform for simulating a variety of tire/road - driving conditions, negating the initial requirement for skid-pan trials when developing algorithms. The fuzzy membership functions were subsequently refined by analysis of the data acquired from the test facility while simulating operation at a high coefficient of friction. The robustness of the fuzzy-logic slip regulator is further tested by applying the resulting controller over a wide range of operating conditions. The results indicate that ABS/traction control may substantially improve longitudinal performance and offer significant potential for optimal control of driven wheels, especially under icy conditions where classical ABS/traction control schemes are constrained to operate very conservatively

    Optimization of a low weight electronic differential for LEVs

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    It is presented a performance analysis of an Electronic Differential (ED) system designed for Light Electric Vehicles (LEVs). We have developed a test tricycle vehicle with one front steering wheel and two rear fixed units is a same axis with a brushless DC integrated in each of them. Each motor has an independent controller unit and a common Arduino electronic CPU based that can plan specific speeds for each wheels as curves are being traced. Different implementations of sensors (input current/torque, steering angle and speed of the wheels) are discussed related to hardware complexity, and performance obtained based on speed level requirements and slipping on the traction wheels.Universidad de Mรกlaga. Campus de Excelencia Internacional Andalucรญa Tech

    Simulation of Electric Vehicles Combining Structural and Functional Approaches

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    In this paper the construction of a model that represents the behavior of an Electric Vehicle is described. Both the mechanical and the electric traction systems are represented using Multi-Bond Graph structural approach suited to model large scale physical systems. Then the model of the controllers, represented with a functional approach, is included giving rise to an integrated model which exploits the advantages of both approaches. Simulation and experimental results are aimed to illustrate the electromechanical interaction and to validate the proposal.Fil: Silva, Luis Ignacio. Consejo Nacional de Investigaciones Cientรญficas y Tรฉcnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingenierรญa. Grupo de Electronica Aplicada; ArgentinaFil: Magallรกn, Guillermo Andrรฉs. Consejo Nacional de Investigaciones Cientรญficas y Tรฉcnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingenierรญa. Grupo de Electronica Aplicada; ArgentinaFil: de la Barrera, Pablo Martin. Consejo Nacional de Investigaciones Cientรญficas y Tรฉcnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingenierรญa. Grupo de Electronica Aplicada; ArgentinaFil: de Angelo, Cristian Hernan. Consejo Nacional de Investigaciones Cientรญficas y Tรฉcnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingenierรญa. Grupo de Electronica Aplicada; ArgentinaFil: Garcia, Guillermo. Consejo Nacional de Investigaciones Cientรญficas y Tรฉcnicas; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Ingenierรญa. Grupo de Electronica Aplicada; Argentin

    Modeling and Simulation of Regenerative Braking Energy in DC Electric Rail Systems

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    Regenerative braking energy is the energy produced by a train during deceleration. When a train decelerates, the motors act as generators and produce electricity. This energy can be fed back to the third rail and consumed by other trains accelerating nearby. If there are no nearby trains, this energy is dumped as heat to avoid over voltage. Regenerative braking energy can be saved by installing energy storage systems (ESS) and reused later when it is needed. To find a suitable design, size and placement of energy storage, a good understanding of this energy is required. The aim of this paper is to model and simulate regenerative braking energy. The dc electric rail transit system model introduced in this paper includes trains, substations and rail systems

    A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

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    ยฉ 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

    Torque distribution strategy for a four In-wheel fully electric car

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    Jornadas de Automรกtica, 2 - 4 de septiembre de 2015. BilbaoElectromobility promises to have a strong impact in several aspects of our life: introducing new means of transport concepts, proposing new business models and allowing to create new vehicle configurations impossible with traditional combustion engines. Regarding the latter, this paper presents a novel torque distribution strategy for a 4 in-wheel electric vehicle which aims to reduce the total longitudinal slip. The control strategy is designed off-line supported by a simulator and tested both in simulation (with a different model from the used for designing) as well as on a real sized prototype. The results show that the total longitudinal slip is successfully reduced after applying the control strategy and additionally, the radius described by the vehicle while cornering is slightly closer to the theoretical Ackerman radius.Ministerio de Economรญa y Competitividad DPI2013-46912-C2-

    Development of Urban Electric Bus Drivetrain

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    The development of the drivetrain for a new series of urban electric buses is presented in the paper. The traction and design properties of several drive variants are compared. The efficiency of the drive was tested using simulation calculations of the vehicle rides based on data from real bus lines in Prague. The results of the design work and simulation calculations are presented in the paper
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