The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Yoichi Hori - One of the best experts on this subject based on the ideXlab platform.

  • four wheel driving force distribution method based on driving stiffness and slip ratio estimation for electric vehicle with in wheel motors
    Vehicle Power and Propulsion Conference, 2012
    Co-Authors: Kenta Maeda, Horishi Fujimoto, Yoichi Hori
    Abstract:

    In this paper, a four-wheel driving force distribution method based on driving stiffness and slip ratio estimation is proposed. In previously proposed distribution method, vehicle velocity is measured by an expensive optical sensor and moreover the response speed of distribution is limited by that of Driving Force Control (DFC), the Traction Control proposed by the authors' research group. Therefore, driving stiffness and slip ratio estimation is applied to improve the distribution method. Due to the slip ratio estimation, vehicle velocity sensor is not needed and the distribution speed depends on that of driving stiffness estimation, which is faster than DFC. If the length of a slippery surface is shorter than the vehicle's wheel base, the total driving force is retained by distributing the shortage of driving force to the wheels that still have Traction. On the other hand, when either the left or right side run on a slippery surface, yaw-moment is suppressed. The effectiveness of the improved method is verified by experiments.

  • electric vehicle Traction Control a new mtte methodology
    IEEE Industry Applications Magazine, 2012
    Co-Authors: Dejun Yin, Yoichi Hori
    Abstract:

    In motion Control of electric vehicles (EVs), the undetectable road conditions and varying vehicle parameters challenge the steering ability and validity. This article investigates a new Traction Control (TC) approach that uses the maximum transmissible torque estimation (MTTE) scheme to carry out the antislip Control of EVs. A closed-loop disturbance observer is employed to enhance the steering stability and to improve the robustness on perturbation in wheel inertia of the MTTE approach. This proposed scheme, which contains the closed-loop friction torque estimator, does not require the use of any differentiator. Additionally, the inversion of the Controlled plant is unnecessary. The real experiment demonstrated the effectiveness and feasibility of the presented antislip strategy.

  • Fault-tolerant Traction Control of electric vehicles
    Control Engineering Practice, 2011
    Co-Authors: Jia-sheng Hu, Dejun Yin, Yoichi Hori
    Abstract:

    Abstract This paper investigates a new Traction Control approach that requires neither chassis velocity nor information about tire–road conditions. Plant fault subject to the uncertainties of the mathematical model and slightly sensor fault are concerned. For general Traction Control of vehicles, the variation of model behavior may break down the steering stability if the chassis velocity is not monitored. This paper presents a fault-tolerant approach based on the maximum transmissible torque estimation (MTTE) scheme which has the ability to prevent electric vehicles from skidding. A PI-type disturbance observer is employed to enhance the steering stability of the MTTE approach. This proposed approach does not require both the differentiator and the inversion of the Controlled plant. Finally, illustrated examples are given for evaluating the fault-tolerant performance and feasibility of the presented anti-slip strategy.

  • a novel Traction Control for ev based on maximum transmissible torque estimation
    IEEE Transactions on Industrial Electronics, 2009
    Co-Authors: Sehoon Oh, Yoichi Hori
    Abstract:

    Controlling an immeasurable state with an indirect Control input is a difficult problem faced in Traction Control of vehicles. Research on motion Control of electric vehicles (EVs) has progressed considerably, but Traction Control has not been so sophisticated and practical because of this difficulty. Therefore, this paper takes advantage of the features of driving motors to estimate the maximum transmissible torque output in real time based on a purely kinematic relationship. An innovative Controller that follows the estimated value directly and constrains the torque reference for slip prevention is then proposed. By analysis and comparison with prior Control methods, the resulting Control design approach is shown to be more effective and more practical, both in simulation and on an experimental EV.

  • Future vehicle driven by electricity and Control - Research on four-wheel-motored "UOT Electric March II"
    IEEE Transactions on Industrial Electronics, 2004
    Co-Authors: Yoichi Hori
    Abstract:

    The electric vehicle (EV) is the most exciting object to apply "advanced motion Control" technique. As an EV is driven by electric motors, it has the following three remarkable advantages: 1) motor torque generation is fast and accurate; 2) motors can be installed in two or four wheels; and 3) motor torque can be known precisely. These advantages enable us to easily realize: 1) high performance antilock braking system and Traction Control system with minor feedback Control at each wheel; 2) chassis motion Control like direct yaw Control; and 3) estimation of road surface condition. "UOT Electric March II" is our novel experimental EV with four in-wheel motors. This EV is made for intensive study of advanced motion Control of an EV.

Steven Dubowsky - One of the best experts on this subject based on the ideXlab platform.

  • Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
    IEEE Transactions on Robotics, 2004
    Co-Authors: Karl Iagnemma, Shinwoo Kang, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a Traction Control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

  • Traction Control of wheeled robotic vehicles in rough terrain with application to planetary rovers
    The International Journal of Robotics Research, 2004
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    Mobile robots are being developed for high-risk missions in rough terrain situations, such as planetary exploration. Here, a rough-terrain Control methodology is presented that exploits the actuator redundancy found in multiwheeled mobile robot systems to improve ground Traction and reduce power consumption. The algorithm optimizes individual wheel torque based on multiple optimization criteria, which are a function of the local terrain profile. A key element of the method is to be able to include estimates of wheel-terrain contact angles and soil characteristics. A method using an extended Kalman filter is presented for estimating these angles using simple on-board sensors. Simulation and experimental results for a micro-rover traversing challenging terrain demonstrate the effectiveness of the algorithm.

  • Mobile Robots in Rough Terrain: Estimation, Motion Planning, and Control with Application to Planetary Rovers
    2004
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    This monograph discusses issues related to estimation, Control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers. Rough terrain roboticsis becoming increasingly important in space exploration, and industrial applications. However, most current motion planning and Control algorithms are not well suited to rough terrain mobility, since they do not consider the physical characteristics of the rover and its environment. Specific addressed topics are: wheel terrain interaction modeling, including terrain parameter estimation and wheel terrain contact angle estimation; rough terrain motion planning; articulated suspension Control; and Traction Control. Simulation and experimental results are presented that show that the desribed algorithms lead to improved mobility for robotic systems in rough terrain.

  • on line terrain parameter estimation for planetary rovers
    International Conference on Robotics and Automation, 2002
    Co-Authors: Karl Iagnemma, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require rovers to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper an on-line estimation method that identifies key terrain parameters using on-board rover sensors is presented. These parameters can be used for accurate traversability prediction or in a Traction Control algorithm. These parameters are also valuable indicators of planetary surface soil composition. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for loose sand.

  • vehicle wheel ground contact angle estimation with application to mobile robot Traction Control
    2000
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    Knowledge of wheel-ground contact angles in vehicles, and in particular mobile robots, is an essential part of many Traction Control algorithms. However, these angles can be difficult to measure directly. Here, a method is presented for estimating wheel-ground contact angles of mobile robots using commonly available on-board sensors. The method utilizes an extended Kalman filter to fuse noisy sensor signals. Simulation and experimental results from a six-wheeled mobile robot demonstrate the effectiveness of the method.

Karl Iagnemma - One of the best experts on this subject based on the ideXlab platform.

  • Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
    IEEE Transactions on Robotics, 2004
    Co-Authors: Karl Iagnemma, Shinwoo Kang, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a Traction Control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

  • Traction Control of wheeled robotic vehicles in rough terrain with application to planetary rovers
    The International Journal of Robotics Research, 2004
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    Mobile robots are being developed for high-risk missions in rough terrain situations, such as planetary exploration. Here, a rough-terrain Control methodology is presented that exploits the actuator redundancy found in multiwheeled mobile robot systems to improve ground Traction and reduce power consumption. The algorithm optimizes individual wheel torque based on multiple optimization criteria, which are a function of the local terrain profile. A key element of the method is to be able to include estimates of wheel-terrain contact angles and soil characteristics. A method using an extended Kalman filter is presented for estimating these angles using simple on-board sensors. Simulation and experimental results for a micro-rover traversing challenging terrain demonstrate the effectiveness of the algorithm.

  • Mobile Robots in Rough Terrain: Estimation, Motion Planning, and Control with Application to Planetary Rovers
    2004
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    This monograph discusses issues related to estimation, Control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers. Rough terrain roboticsis becoming increasingly important in space exploration, and industrial applications. However, most current motion planning and Control algorithms are not well suited to rough terrain mobility, since they do not consider the physical characteristics of the rover and its environment. Specific addressed topics are: wheel terrain interaction modeling, including terrain parameter estimation and wheel terrain contact angle estimation; rough terrain motion planning; articulated suspension Control; and Traction Control. Simulation and experimental results are presented that show that the desribed algorithms lead to improved mobility for robotic systems in rough terrain.

  • on line terrain parameter estimation for planetary rovers
    International Conference on Robotics and Automation, 2002
    Co-Authors: Karl Iagnemma, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require rovers to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper an on-line estimation method that identifies key terrain parameters using on-board rover sensors is presented. These parameters can be used for accurate traversability prediction or in a Traction Control algorithm. These parameters are also valuable indicators of planetary surface soil composition. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for loose sand.

  • vehicle wheel ground contact angle estimation with application to mobile robot Traction Control
    2000
    Co-Authors: Karl Iagnemma, Steven Dubowsky
    Abstract:

    Knowledge of wheel-ground contact angles in vehicles, and in particular mobile robots, is an essential part of many Traction Control algorithms. However, these angles can be difficult to measure directly. Here, a method is presented for estimating wheel-ground contact angles of mobile robots using commonly available on-board sensors. The method utilizes an extended Kalman filter to fuse noisy sensor signals. Simulation and experimental results from a six-wheeled mobile robot demonstrate the effectiveness of the method.

Weiqiang Yue - One of the best experts on this subject based on the ideXlab platform.

  • tire road friction estimation and Traction Control strategy for motorized electric vehicle
    PLOS ONE, 2017
    Co-Authors: Liqiang Jin, Mingze Ling, Weiqiang Yue
    Abstract:

    In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque Control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to Traction Control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with Traction Control system (TCS).

H. Shibly - One of the best experts on this subject based on the ideXlab platform.

  • Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
    IEEE Transactions on Robotics, 2004
    Co-Authors: Karl Iagnemma, Shinwoo Kang, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a Traction Control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

  • on line terrain parameter estimation for planetary rovers
    International Conference on Robotics and Automation, 2002
    Co-Authors: Karl Iagnemma, H. Shibly, Steven Dubowsky
    Abstract:

    Future planetary exploration missions will require rovers to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper an on-line estimation method that identifies key terrain parameters using on-board rover sensors is presented. These parameters can be used for accurate traversability prediction or in a Traction Control algorithm. These parameters are also valuable indicators of planetary surface soil composition. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for loose sand.