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Viewing 1 to 30 of 116
2017-03-28
Technical Paper
2017-01-1113
Yulong Lei, Pengxiang Song, Hongpeng Zheng, Yao Fu, Zhenjie Liu, Xuanyi Fu
Abstract Hydraulic retarders have been widely used in heavy-duty vehicles because of its advantages such as large braking torque and long operating hours. They can be used instead of service brakes in non-emergency braking conditions and can also reduce frequency and time of driver’s actions in braking process, thereby minimizing heat-related problems. In order to accurately produce braking torque needed for the vehicle in time by using hydraulic retarder, which enable the vehicle to travel stably and safely during downhill driving, aiming at the constant-speed function of hydraulic retarder, the research of constant-speed control method is conducted in this paper. The structure and working principle of hydraulic retarder is introduced and the dynamic characteristic is analyzed. And the theoretical model of vehicle and hydraulic retarder are established based on dynamic analysis of the vehicle downhill driving.
2017-03-28
Journal Article
2017-01-0241
Thiago B. Murari, Paulo Ungaretti, Marcelo A. Moret
Abstract Geometric Dimensioning and Tolerancing is used to describe the allowed feature variations regarding the product design. Tolerance specification is important in many stages of all phases on product development. The product development engineering need to define the symbols to use on the Feature Control Frame of every component. Since the component function has an increment on its complexity year over year, it is not trivial to define those symbols anymore. The determination of dimensional tolerance shall be preceded by careful specification of the types of tolerance and symbols that will be applied in controlled features. Poor tolerance specifications can increase the production cost, require late product changes or lead to legal issues.
2017-03-28
Journal Article
2017-01-1569
Amro Elhefnawy, Alhossein sharaf, Hossam Ragheb, Shawky Hegazy
Abstract This paper presents an advanced control system, which integrates three fuzzy logic controllers namely; Direct Yaw-moment Control (DYC), Active Roll-moment Control (ARC) and Active Front Steering (AFS) to enhance vehicle cornering and overturning stability. Based on a well-developed and validated fourteen degree of freedom (DOF) full vehicle model with non-linear tire characteristics, a reference 3-DOF yaw-roll plane vehicle model is introduced to control yaw rate, sideslip angle, and roll angle of the vehicle body. The control actions of both direct yaw and active roll moments are performed by generating differential braking moments across the front wheels, while the control action of the active steering is performed by modifying the steering wheel angle. Different standard cornering tests are conducted in MATLAB / Simulink environment such as J-turn, fishhook and lane change maneuvers.
2017-03-28
Journal Article
2017-01-0412
Mina M.S. Kaldas, Kemal Çalışkan, Roman Henze, Ferit Küçükay
Abstract Semi-active suspension offers variety of damping force range which demands greater need to optimize the top mount to ensure multiple objectives of ride comfort, harshness and safety can be achieved. For this purpose, this paper proposes a numerical optimization procedure for improving the harshness performance of the vehicle through the adjustment of the damper top mount characteristics of the semi-active suspension system. The proposed optimization process employs a frequency dependent combined objective function based on ride comfort and harshness evaluation. A detailed and accurate damper top mount mathematical model is implemented inside a validated full vehicle model to provide a realistic simulation environment for the optimization study. The semi-active suspension system employs a Rule-Optimized Fuzzy-Logic controller. The ride comfort and harshness of the full vehicle are evaluated by analyzing the body acceleration in different frequency ranges.
2017-01-10
Technical Paper
2017-26-0349
Rushil Batra, Sahil Nanda, Shubham Singhal, Ranganath Singari
Abstract This study is an attempt to develop a decision support and control structure based on fuzzy logic for deployment of automotive airbags. Airbags, though an additional safety feature in vehicles, have proven to be fatal at various instances. Most of these casualties could have been avoided by using seat belts in the intended manner that is, as a primary restraint system. Fatalities can be prevented by induction of smart systems which can sense the presence and differentiate between passengers and conditions prevailing at a particular instant. Fuzzy based decision making has found widespread use due to its ability to accept non-binary or grey data and compute a reliable output. Smart airbags also allow the Airbag Control Unit to control inflation speed depending on instantaneous conditions.
2017-01-10
Technical Paper
2017-26-0081
Karthikeyan Nagarajan
Abstract The objective of this work is to develop a realistic driver model which helps in simulating drive related behavior of system vehicle and other vehicles in a traffic simulation environment. A driver model is said to be realistic only if it can learn and adapt to any variations in vehicle parameters and simulated road conditions. At the same time, the control action and the learning should represent human-like computation. In this paper, the proposed driver model consists of a Self-Learning Model Reference Fuzzy Longitudinal and Lateral controller. The model employs a set of fuzzy rules to realize a path-following lateral controller whereas the longitudinal control is governed by another set of fuzzy rules. The adaptive capabilities of the model are realized using supervisory fuzzy set and simple self-learning algorithm. This adaptive mechanism evaluates the current controller performance against the desired closed loop reference model.
2016-10-17
Technical Paper
2016-01-2222
Eduardo D. Marquez, Douglas Nelson
Abstract The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently developing a control strategy for a parallel plug-in hybrid electric vehicle (PHEV). The hybrid powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. Fuzzy rule sets determine the torque split between the motor and the engine using the accelerator pedal position, vehicle speed and state of charge (SOC) as the input variables. The torque producing components are a 280 kW V8 L83 engine with active fuel management (AFM) and a post-transmission (P3) 100 kW custom motor. The vehicle operates in charge depleting (CD) and charge sustaining (CS) modes. In CD mode, the model drives as an electric vehicle (EV) and depletes the battery pack till a lower state of charge threshold is reached. Then CS operation begins, and driver demand is supplied by the engine operating in V8 or AFM modes with supplemental or loading torque from the P3 motor.
2016-04-05
Technical Paper
2016-01-1676
Wenchao Liu, Guoying Chen, Changfu Zong, Chunshan Li
Abstract The driving range of the electric vehicle (EV) greatly restricts the development of EVs. The vehicles waste plenty of energy on account of automobiles frequently braking under the city cycle. The regenerative braking system can convert the braking kinetic energy into the electrical energy and then returns to the battery, so the energy regeneration could prolong theregenerative braking system. According to the characteristics of robustness in regenerative braking, both regenerative braking and friction braking based on fuzzy logic are assigned after the front-rear axle’s braking force is distributed to meet the requirement of braking security and high-efficient braking energy regeneration. Among the model, the vehicle model and the mechanical braking system is built by the CRUISE software. The paper applies the MATLAB/SIMULINK to establish a regenerative braking model, and then selects the UEDC city cycle for model co-simulation analysis.
2016-04-05
Journal Article
2016-01-0444
Kemal Çalışkan, Mina M.S. Kaldas, Roman Henze, Ferit Küçükay
Abstract This paper presents a performance analysis study for the Rule-Optimized controller of a semi-active suspension system. The Rule-Optimized controller is based on a Fuzzy Logic control scheme which offers new opportunities in the improvement of vehicle ride performance. An eleven degree of freedom full vehicle ride dynamics model is developed and validated through laboratory tests performed on a hydraulic four-poster shaker. An optimization process is applied to obtain the optimum Fuzzy Logic membership functions and the optimum rule-base of the semi-active suspension controller. The global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle is determined through discrete optimization with Genetic Algorithm (GA).
2016-04-05
Journal Article
2016-01-0433
Tao Sun, Eungkil Lee, Yuping He
Abstract This paper presents nonlinear bifurcation stability analysis of articulated vehicles with active trailer differential braking (ATDB) systems. ATDB systems have been proposed to improve stability of articulated vehicle systems to prevent unstable motion modes, e.g., jack-knifing, trailer sway and rollover. Generally, behaviors of a nonlinear dynamic system may change with varying parameters; a stable equilibrium can become unstable and a periodic oscillation may occur or a new equilibrium may appear making the previous equilibrium unstable once the parameters vary. The value of a parameter, at which these changes occur, is known as “bifurcation value” and the parameter is known as the “bifurcation parameter”. Conventionally, nonlinear bifurcation analysis approach is applied to examine the nonlinear dynamic characteristics of single-unit vehicles, e.g., cars, trucks, etc.
2016-04-05
Technical Paper
2016-01-1203
Zhang Qiao, Weiwen Deng, Jian Wu, Feng Ju, Jingshan Li
Abstract This paper describes a novel power management control strategy of battery and supercapacitor hybrid energy storage system to improve system efficiency and battery lifetime. In the presented research, the high and low frequency power demand in the load is separated by a Haar wavelet transform algorithm to overcome the problem of battery overload work and associated degeneration in battery lifetime resulting from an ineffective distribution between battery and supercapacitor. The purpose of frequency distribution is that the supercapacitor is used to share high frequency power components of load power demand to smooth the power demand applied to battery. However, the sole frequency control often fails to realize the optimal utilization of supercapacitor because of the uncertain variation in the driving cycle.
2016-04-05
Technical Paper
2016-01-0874
Giuseppe Quaremba, Luigi Allocca, Amedeo Amoresano, Vincenzo Niola, Alessandro Montanaro, Giuseppe Langella
Abstract Advanced numerical techniques, such as fuzzy logic and neural networks have been applied in this work to digital images acquired on a mono-component fuel spray (iso-octane), in order to define, in a stochastic way, the gas-liquid interface evolution. The image is a numerical matrix and so it is possible to characterize geometrical parameters and the time evolution of the jet by using deterministic, statistical stochastic and other several kinds of approach. The algorithm used works with the fuzzy logic concept to binarize the shades gray of the pixel, depending them, by using the schlieren technique, on the gas density. Starting from a primary fixed threshold, the applied technique, can select the ‘gas’ pixel from the ‘liquid’ pixel and so it is possible define the first most probably boundary lines of the spray.
2016-04-05
Journal Article
2016-01-1655
Benjamin Hirche, Beshah Ayalew
This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.
2016-04-05
Journal Article
2016-01-1630
Benjamin Hirche, Beshah Ayalew
In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).
2016-04-05
Technical Paper
2016-01-1654
Umair Hussain Syed, Alessandro Vigliani
Abstract Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.
2016-02-01
Technical Paper
2016-28-0035
Shraddhesh Rasal, Jayanth Jaganmohan, Sohan Agashe, Kiran P Wani
Abstract The design of the conventional passive suspension has always been a compromise between vehicle handling and comfort, which led to the development of the modern active and semi active suspension systems. Amongst these, semi-active suspension has been focus of research in recent years owing to its lesser complexity and less power consumption as compared to active suspension. Semi active suspension uses real time variation in damping coefficient which can be achieved by using various control strategies. It is observed from available literature that Skyhook (for better ride comfort), Groundhook (for better vehicle handling) and Hybrid are most widely used strategies. These strategies use ‘On-Off’ control strategy (i.e. two preset values of damping co-efficient) but a better control over damping coefficients can be achieved using Continuous Control strategy. This paper aims to implement Continuous control strategy using Fuzzy logic for the semi active suspension.
2015-09-22
Technical Paper
2015-36-0270
Hebert Azevedo Sá, Mauro Speranza Neto, Marco Antonio Meggiolaro, Armando Morado Ferreira
Abstract Semi-autonomous control systems applied to automobiles are Advanced Driver Assistance Systems (ADAS) that have gained importance from similar devices with applications in robotics. The control sharing between humans and automatic controllers is the main characteristic of these systems, and can be accomplished through various different manners. However, the use of Artificial Intelligence (AI) techniques for this purpose remains unexplored. In this paper we propose the design of a semi-autonomous control system applied to military vehicles through the use of Fuzzy Inference Systems for the definition of the controller intervention level. Simulations of a vehicle being operated in highly dangerous situations, represented by the existence of hostile military threats or by unexpected maneuvers that could put the stability of the car at risk were performed.
2015-09-15
Technical Paper
2015-01-2441
Ahmet Oztekin
Abstract This paper outlines an analytical framework to perform a data-driven, risk-based assessment of Air Traffic Control (ATC) facilities. Safety associated with an ATC facility is modeled as an influence network using a set of risk factors. A novel hybrid approach employing Adaptive-Network based Fuzzy Inference Systems is introduced to propagate the model. Statistical analysis of system-wide data for each risk factor is performed to identify outliers and understand underlying distributions. They are then used to define Fuzzy Membership Functions for model variables. Analytical Hierarch Process (AHP) is used to determine rules required by the model's inference engine. Finally, the methodology is applied to a set of ATC facilities using real data.
2015-06-15
Journal Article
2015-01-2260
Tianze Shi, Shuming Chen, Dengfeng Wang
Abstract Artificial intelligence systems are highly accepted as a technology to offer an alternative way to tackle complex and non-linear problems. They can learn from data, and they are able to handle noisy and incomplete data. Once trained, they can perform prediction and generalization at high speed. The aim of the present study is to propose a novel approach utilizing the adaptive neuro-fuzzy inference system (ANFIS) and the fuzzy clustering method for automotive ride performance estimation. This study investigated the relationship between the automotive ride performance and relative parameters including speed, spring stiffness, damper coefficients, ratios of sprung and unsprung mass. A Takagi-Sugeno fuzzy inference system associated with artificial neuro network was employed. The C-mean fuzzy clustering method was used for grouping the data and identifying membership functions.
2015-05-01
Journal Article
2015-01-9082
Branislav Sredanovic, Djordje Cica
Abstract The most efficient way to reduce friction and heat generation at the cutting zone is to use advanced cooling and lubricating techniques. In this paper, an experimental study was performed to investigate the capabilities of conventional, minimal quantity lubrication (MQL) and high pressure cooling (HPC) in the turning operations. Process parameters (feed, cutting speed and depth of cut) are used as inputs to the developed artificial neural network (ANN) and the adaptive networks based fuzzy inference systems (ANFIS) model for prediction of cutting forces, tool life and surface roughness. Results obtained by the models have been compared for their prediction capability with the experimentally determined values and very good agreement with experimental results was observed.
2015-04-14
Technical Paper
2015-01-0207
Xiping Ma, Zhenchun Xia, Haotian Wu, Xianan Huang
Abstract Powertrain diagnosis has been demanded with growth & complexity of powertrain electronic control system and enforcement of law & regulation in the last decades. In regulation OBD II, requirement of misfire monitoring has been demanded much more strictly. A variety of diagnosis methods for misfire have been proposed and developed, however most of them either depend greatly on special or expensive sensors or suffer from the disturbance of vibration due to non-misfire reasons. One combination of Frequency Domain Analysis and Fuzzy Logic to perform the misfire diagnosis is proposed. It takes full advantage of property of frequency domain analysis and fuzzy logic, providing accurate and robust detection results, without adding additional hardware diagnosis instruments.
2015-04-14
Journal Article
2015-01-0621
Mina M.S. Kaldas, Kemal Çalışkan, Roman Henze, Ferit Küçükay
Abstract There is an increasing customer demand for adjustable chassis control features which enable adaption of the vehicle comfort and driving characteristics to the customer requirements. One of the most promising vehicle control systems which can be used to change the vehicle characteristics during the drive is the semi-active suspension system. This paper presents a Rule-Optimized Fuzzy Logic controller for semi-active suspension systems which can continuously adjust itself not only according to the road conditions but also to the driver requirements. The proposed controller offers three different control modes (Comfort, Normal and Sport) which can be switched by the driver during driving. The Comfort Mode minimizes the accelerations imposed on the driver and passengers by using a softer damping. On the other hand, the increased damping in Sport Mode provides better road holding capability, which is critical for sporty handling.
2014-11-11
Technical Paper
2014-32-0020
Patrick Falk, Christian Hubmann
Abstract Originally developed for the automotive market, a fully automatic real-time measurement tool AVL-DRIVE is commercially available for analyzing and scoring vehicle drive quality, also known as “Driveability”. This system from AVL uses its own transducers, calibrated to the sensitivity and response of the human body to measure the forces felt by the driver, such as acceleration, shock, surging, vibration, noise, etc. Simultaneously, the vehicle operating conditions are measured, (throttle grip angle, engine speed, gear, vehicle speed, temperature, etc.). Because the software is pre-programmed with the scores from a multitude of different vehicles in each vehicle class via neural networks and fuzzy logic formula, a quality score with reference to similar competitor vehicles is instantly given. This tool is already successfully implemented in the market for years to investigate such driveability parameters for passenger cars.
2014-09-30
Technical Paper
2014-36-0359
Alessandro Cezar Pinto, Geovanni Vezzaro Mattioli
Abstract This paper describes the development of an Intelligent Traffic Lights Control System using Fuzzy Logic concepts. Fuzzy Logic offers the possibility to ‘compute with words’, by using a mechanism for representing linguistic constructs common on real world problems. This is very important when the complexity of a task (problem) exceeds a certain threshold. Real world complex problems such human controlled systems involve a certain degree of uncertainty, which cannot be handled by traditional binary set theory. The algorithm implementation will be done inside Mathworks MATLAB software, and the results will be measured on Simulink Tool to create traffic scenarios and comparisons between simple time-based algorithms and the proposed system. During Project phase, a Robustness Parameter-Diagram will be used to design the system and cover its variables, error states, possible noises and control factors.
2014-09-30
Technical Paper
2014-01-2291
Dong Zhang, Changfu Zong, Guoying Chen, Pan Song, Zexing Zhang
Abstract A full drive-by-wire electric vehicle, named Urban Future Electric Vehicle (UFEV) is developed, where the four wheels' traction and braking torques, four wheels' steering angles, and four active suspensions (in the future) are controlled independently. It is an ideal platform to realize the optimal vehicle dynamics, the marginal-stability and the energy-efficient control, it is also a platform for studying the advanced chassis control methods and their applications. A centralized control system of hierarchical structure for UFEV is proposed, which consist of Sensor Layer, Identification and Estimation Layer, Objective Control Layer, Forces and Motion Distribution Layer, Executive Layer. In the Identification and Estimation Layer, identification model is established by utilizing neural network algorithms to identify the driver characteristics. Vehicle state estimation and road identification of UFEV based on EKF and Fuzzy Logic Control methods is also conducted in this layer.
2014-09-16
Technical Paper
2014-01-2174
Nicholas Ernest, Kelly Cohen, Corey Schumacher, David Casbeer
Abstract Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) for future applications, it becomes apparent that on-board intelligent controllers will be necessary for these advanced systems. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent managers for these advanced unmanned craft through the novel means of a genetic cascading fuzzy system. In this approach, a genetic algorithm creates rule bases and optimizes membership functions for multiple fuzzy logic systems, whose inputs and outputs feed into one another alongside crisp data. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs intelligent controllers.
2014-04-01
Technical Paper
2014-01-1742
Yao Fu, Yulong Lei, Ke Liu, Yuanxia Zhang, Huabing Zeng
Abstract In a traditional shift control strategy, the gear range is selected based on the throttle opening and the vehicle speed. The disadvantage of two-parameter based system is that the shift map is lack of adaptability in certain special conditions. The driving environment and the true intentions of the drivers are not fully taken into account by the shift control system. Therefore, improving the feasibility of the shift control strategy for the true intentions of the driver and driving environment is of great significance. Under braking conditions, Automatic transmission shift map with two parameters is unable to use engine braking effectively, which affects the drivability and safety of vehicles greatly. This paper presents a newly developed shift control strategy under braking conditions. First of all, the necessity of engine braking was analyzed.
2014-04-01
Technical Paper
2014-01-1909
Rashad Mustafa, Mirko Schulze, Peter Eilts, Ferit Küçükay
Abstract Hybrid electric vehicles (HEV's) are facing increasing challenges in optimizing the energy flow through a vehicle system, in order to improve both fuel economy and vehicle emissions. Energy management of HEV's is a difficult task due to the complexity of the total system in terms of electrical, mechanical and thermal behavior. In this paper, an advanced control strategy for a parallel hybrid vehicle is developed. Four main steps are presented, particularly to achieve a reduction in fuel consumption. The first step is the development of a highly complex HEV model, including dynamic and thermal behavior. Second, a heuristical control strategy is developed to determine the HEV modes and third, a State of Charge (SoC) leveling is developed with the interaction of a fuzzy logic controller. It is proposed to calculate the load point shifting of the Internal Combustion Engine (ICE) and the desired battery SoC.
2014-04-01
Journal Article
2014-01-0083
Lu Fan, Bing Zhou, Harry Zheng
In vehicles equipped with conventional Electric Power Steering (EPS) systems, the steering effort felt by the driver can be unreasonably low when driving on slippery roads. This may lead inexperienced drivers to steer more than what is required in a turn and risk losing control of the vehicle. Thus, it is sensible for tire-road friction to be accounted for in the design of future EPS systems. This paper describes the design of an auxiliary EPS controller that manipulates torque delivery of current EPS systems by supplying its motor with a compensation current controlled by a fuzzy logic algorithm that considers tire-road friction among other factors. Moreover, a steering system model, a nonlinear vehicle dynamics model and a Dugoff tire model are developed in MATLAB/Simulink. Physical testing is conducted to validate the virtual model and confirm that steering torque decreases considerably on low friction roads.
2014-04-01
Journal Article
2014-01-0868
Mina Kaldas, Kemal Caliskan, Roman Henze, Ferit Küçükay
Abstract New developments in road profile measurement systems and in semi-active damper technology promote the application of preview control strategies to vehicle suspension systems. This paper details a new semi-active suspension control approach in which a rule-optimized Fuzzy Logic controller is enhanced through preview capability. The proposed approach utilizes an optimization process for obtaining the optimum membership functions and the optimum rule-base of the preview enhanced Fuzzy Logic controller. The preview enhanced Fuzzy Logic controller uses the feedforward road input information and the feedback vehicle state information as the controller inputs. An eleven degree of freedom full vehicle model, which is validated through laboratory tests performed on a hydraulic four-poster shaker, is used for the controller synthesis.
Viewing 1 to 30 of 116

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