The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform

Massimo Losa - One of the best experts on this subject based on the ideXlab platform.

  • Peak Friction Prediction Model Based on Surface Texture Characteristics
    Transportation Research Record, 2015
    Co-Authors: Pietro Leandri, Massimo Losa
    Abstract:

    This paper proposes a new model for predicting the speed gradient of peak friction values on asphalt pavements on the basis of surface characteristics. The innovative feature of the proposed model is the reliable estimation of peak friction values experienced by vehicles equipped with an Antilock Brake System at a certain vehicle speed. To define the experimental model, several types of dense asphalt concrete surface layers with various surface characteristics were analyzed by in situ tests. Friction was measured with the Skiddometer BV11 and the British pendulum tester, and texture properties were measured with a laser profilometer. The Rado model was used to predict peak friction values at three vehicle speeds, and these data were used to determine the gradient of peak friction values for each pavement section. The spectral analysis of pavement profile data was used to define a texture parameter negatively correlated with peak friction values; this parameter was introduced in a new formulation of the sp...

  • Peak Friction Prediction Model Based on Surface Texture Characteristics
    Transportation Research Record: Journal of the Transportation Research Board, 2015
    Co-Authors: Pietro Leandri, Massimo Losa
    Abstract:

    This paper proposes a new model for predicting the speed gradient of peak friction values on asphalt pavements on the basis of surface characteristics. The innovative feature of the proposed model is the reliable estimation of peak friction values experienced by vehicles equipped with an Antilock Brake System at a certain vehicle speed. To define the experimental model, several types of dense asphalt concrete surface layers with various surface characteristics were analyzed by in situ tests. Friction was measured with the Skiddometer BV11 and the British pendulum tester, and texture properties were measured with a laser profilometer. The Rado model was used to predict peak friction values at three vehicle speeds, and these data were used to determine the gradient of peak friction values for each pavement section. The spectral analysis of pavement profile data was used to define a texture parameter negatively correlated with peak friction values; this parameter was introduced in a new formulation of the speed number Sp* that was a measure of the influence of pavement macrotexture on peak friction values. The speed number Sp* was used in the new exponential model proposed for defining the gradient of peak friction values. The results show that the model is highly reliable; because the model allows identification of texture characteristics to be modified to optimize peak friction values, it is particularly useful for optimization of the mix design and maintenance of pavement surfaces.

Seibum B Choi - One of the best experts on this subject based on the ideXlab platform.

  • development of an Antilock Brake System for electric vehicles without wheel slip and road friction information
    IEEE Transactions on Vehicular Technology, 2019
    Co-Authors: Kyoungseok Han, Byunghwan Lee, Seibum B Choi
    Abstract:

    This paper presents a control method of an Antilock Brake System (ABS) for electric vehicles. For decades, serious efforts have been dedicated to designing a wheel slip-based ABS controller, but there are some inherent flaws. To realize a robust control System, the wheel slip and road friction information are generally required. Unfortunately, however, these parameters cannot be accurately measured in production vehicles. The method suggested in this paper is aimed at solving these problems by exploiting the nonlinear characteristics of tire force. The optimal wheel slip can thereby be found without wheel slip and road friction information. We employ the motor as an actuator instead of a conventional hydraulic Brake System at the front wheels. However, the rear wheels are still hydraulically controlled. That is, the front and rear wheels have different roles in the proposed method. This hardware configuration can be changed for control purposes, so the proposed approach is not designed for a specific hardware configuration. The performance of the proposed method is confirmed by simulations and real vehicle-based experiments.

  • Antilock Brake System with a continuous wheel slip control to maximize the braking performance and the ride quality
    IEEE Transactions on Control Systems and Technology, 2008
    Co-Authors: Seibum B Choi
    Abstract:

    In this paper, a new type of Antilock Brake System (ABS) algorithm is developed. A full-time feedback control algorithm differentiates the new ABS from rule-based conventional ABS algorithms. The rear wheels are controlled to create limit cycles around the peak friction slip points. From the cycling patterns of the rear wheels, the optimal slips are defined. The front wheels are controlled to track the optimal slips defined by monitoring the behaviors of the rear wheels. The new algorithm can be implemented on any production ABS hardware without any modification or extra sensors. The test results show significant performance improvement in both the stopping distance and the noise, vibration, and harshness on homogeneous surfaces, and also quick detection of surface transition. The robustness of the new ABS algorithm is proven by vehicle tests on various speeds, surfaces, and driving conditions.

Philippe Bonnifait - One of the best experts on this subject based on the ideXlab platform.

  • Road selection using multicriteria fusion for the road-matching problem
    IEEE Transactions on Intelligent Transportation Systems, 2007
    Co-Authors: Mayssam El Najjar, Philippe Bonnifait
    Abstract:

    This paper presents a road selection strategy for novel road-matching methods that are designed to support real-time navigational features within Advanced Driving-Assistance Systems (ADAS). Selecting the most likely segment(s) is a crucial issue for the road-matching problem. The selection strategy merges several criteria using Belief theory. Particular attention is given to the development of belief functions from measurements and estimations of relative distances, headings, and velocities. Experimental results using data from Antilock Brake System sensors, the differential Global Positioning System receiver, and the accurate digital roadmap illustrate the performances of this approach, particularly in ambiguous situations

  • Road Selection using Multi-Criteria Fusion for the Roadmap-Matching Problem
    IEEE Transactions on Intelligent Transportation Systems, 2007
    Co-Authors: Maan El Badaoui El Najjar, Philippe Bonnifait
    Abstract:

    This paper presents a road selection strategy for novel road-matching methods that are designed to support real-time navigational features within Advanced Driving-Assistance Systems (ADAS). Selecting the most likely segment(s) is a crucial issue for the road-matching problem. The selection strategy merges several criteria using Belief theory. Particular attention is given to the development of belief functions from measurements and estimations of relative distances, headings, and velocities. Experimental results using data from Antilock Brake System sensors, the differential Global Positioning System receiver, and the accurate digital roadmap illustrate the performances of this approach, particularly in ambiguous situations.

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

  • Designing a genetic neural fuzzy Antilock-Brake-System controller
    IEEE Transactions on Evolutionary Computation, 2002
    Co-Authors: Yonggon Lee, Stanislaw H. Zak
    Abstract:

    A typical Antilock Brake System (ABS) senses when the wheel lockup is to occur, releases the Brakes momentarily, and then reapplies the Brakes when the wheel spins up again. In this paper, a genetic neural fuzzy ABS controller is proposed that consists of a nonderivative neural optimizer and fuzzy-logic components (FLCs). The nonderivative optimizer finds the optimal wheel slips that maximize the road adhesion coefficient. The optimal wheel slips are for the front and rear wheels. The inputs to the FLC are the optimal wheel slips obtained by the nonderivative optimizer. The fuzzy components then compute Brake torques that force the actual wheel slips to track the optimal wheel slips; these torques minimize the vehicle stopping distance. The FLCs are tuned using a genetic algorithm. The performance of the proposed controller is compared with the case when maximal Brake torques are applied causing a wheel lockup, and with the case when wheel slips are kept constant while the road surface changes.

  • Antilock Brake System MODELLING AND FUZZY CONTROL
    International Journal of Vehicle Design, 2000
    Co-Authors: Anthony B. Will, Stanislaw H. Zak
    Abstract:

    A vehicle braking model for straight line braking analysis is presented. This model includes the longitudinal vehicle dynamics, tyre dynamics, and road surface model. The developed model is tested on an asphalt surface on a step Brake input. A fuzzy logic Antilock Brake System (ABS) controller is proposed to minimize the stopping distance under emergency braking conditions. The performance of the fuzzy logic controller with a manual Brake System in an emergency braking manoeuvre is compared. (A)

  • SLIDING MODE WHEEL SLIP CONTROLLER FOR AN Antilock BRAKING System
    International Journal of Vehicle Design, 1998
    Co-Authors: A B Will, S Hui, Stanislaw H. Zak
    Abstract:

    A nonlinear control System that combines a sliding mode based optimiser and a proportional–plus–integral–plus–derivative (PID) controller is presented for a vehicle Antilock Brake System. The sliding mode optimiser performs an on–line search for the optimal wheel slip that corresponds to the vehicle's maximum deceleration. The PID controller and the sliding mode optimiser are coupled to regulate the vehicle's Brake torque to control the wheel slip to its optimal value. The performance of the proposed control schemes is illustrated with simulation examples.

Pietro Leandri - One of the best experts on this subject based on the ideXlab platform.

  • Peak Friction Prediction Model Based on Surface Texture Characteristics
    Transportation Research Record, 2015
    Co-Authors: Pietro Leandri, Massimo Losa
    Abstract:

    This paper proposes a new model for predicting the speed gradient of peak friction values on asphalt pavements on the basis of surface characteristics. The innovative feature of the proposed model is the reliable estimation of peak friction values experienced by vehicles equipped with an Antilock Brake System at a certain vehicle speed. To define the experimental model, several types of dense asphalt concrete surface layers with various surface characteristics were analyzed by in situ tests. Friction was measured with the Skiddometer BV11 and the British pendulum tester, and texture properties were measured with a laser profilometer. The Rado model was used to predict peak friction values at three vehicle speeds, and these data were used to determine the gradient of peak friction values for each pavement section. The spectral analysis of pavement profile data was used to define a texture parameter negatively correlated with peak friction values; this parameter was introduced in a new formulation of the sp...

  • Peak Friction Prediction Model Based on Surface Texture Characteristics
    Transportation Research Record: Journal of the Transportation Research Board, 2015
    Co-Authors: Pietro Leandri, Massimo Losa
    Abstract:

    This paper proposes a new model for predicting the speed gradient of peak friction values on asphalt pavements on the basis of surface characteristics. The innovative feature of the proposed model is the reliable estimation of peak friction values experienced by vehicles equipped with an Antilock Brake System at a certain vehicle speed. To define the experimental model, several types of dense asphalt concrete surface layers with various surface characteristics were analyzed by in situ tests. Friction was measured with the Skiddometer BV11 and the British pendulum tester, and texture properties were measured with a laser profilometer. The Rado model was used to predict peak friction values at three vehicle speeds, and these data were used to determine the gradient of peak friction values for each pavement section. The spectral analysis of pavement profile data was used to define a texture parameter negatively correlated with peak friction values; this parameter was introduced in a new formulation of the speed number Sp* that was a measure of the influence of pavement macrotexture on peak friction values. The speed number Sp* was used in the new exponential model proposed for defining the gradient of peak friction values. The results show that the model is highly reliable; because the model allows identification of texture characteristics to be modified to optimize peak friction values, it is particularly useful for optimization of the mix design and maintenance of pavement surfaces.