Optimal Wheel Slip Research Articles

A Simplified Approach to the Evaluation of the Influences of Key Factors on Agricultural Tractor Fuel Consumption during Heavy Drawbar Tasks under Field Conditions

The optimization of energy input on agricultural farms, such as through improved fuel consumption, is currently under investigation in agricultural mechanization research with the aim of achieving economic and environmental goals. In previous research, we developed a simplified algorithm focused on defining the most efficient tractor–implement combination considering the factors that most influence this aspect. The ASABE (American Society of Agricultural and Biological Engineers) equation for calculating the drawbar pull force was adopted to fit the results to the soil conditions. Agricultural tires of different sizes were tested at different pressure settings under field conditions to assess differences in drawbar force. The resulting algorithm underwent a linear regression analysis to achieve a simplified equation for assessing the optimal wheel-slip, mass, engine power, and tire pull force properties during drawbar works that result in optimal fuel consumption with a minimal tractor efficiency impairment. Using a specific probability density function, the Monte Carlo Simulation method introduced randomness into the input and runs a sufficiently large number of trials to identify the most probable output. The result is a simplified algorithm that can be used to investigate the effects of certain parameters on fuel consumption; however, it can be adapted to evaluate the effects of different implements, tires, engine settings, or fleet management methods on fuel consumption.

Integrated control of braking and steering systems to improve vehicle stability based on optimal wheel slip ratio estimation

Integrated control of braking and steering systems to improve vehicle stability based on optimal wheel slip ratio estimation

Adjustable Gain Enhanced Fuzzy Logic Controller for Optimal Wheel Slip Ratio Tracking in Hard Braking Control System

This paper has presented hard braking control system based on Adjustable Gain Enhanced Fuzzy Logic Controller (AGE-FLC) for optimal wheel slip ratio tracking performance. The purpose of the study was to improve slip ratio tracking and eliminate cycling while achieving very much shortened distance during emergency braking. The model of a braking vehicle at speed of 30 m.s^-1 subject to wheel locking was developed and implemented in MATLAB/Simulink environment. Simulation was conducted without a controller to study the slip ratio performance of the system on different road surfaces. The simulation results showed that stopping distance was 135.2 m in 5 seconds. A Fuzzy Logic Controller (FLC) whose control signal was enhanced by adding an adjustable gain mechanism to its output was designed. Simulation results showed that the AGE-FLC controller offered optimal tracking of desired wheel slip ratio of 0.1 as fast as possible on all road surface scenarios, while improving the stopping distance by 70.4% on dry road surface, 63.3% on wet road surface, 57.5% on cobblestone road surface and 48.8% on snow road surface in 2.651seconds.

Wheel slip ratio regulation for investigating the vehicle's dynamic behavior during braking and steering input

In this study, the vehicle's dynamic behavior during braking and steering input is investigated by considering the quarter-car model. The case study for this research is a Sport-Utility Vehicle (SUV) with the anti-lock braking system (ABS) and nonlinear dynamic equations are considered for it along with Pacejka tire model. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet and icy) during braking is considered as the ABS control strategy. In order to regulating the wheel slip ratio in the optimal value, an intelligent adaptive fuzzy controller that can perform online parameter estimation is considered. In this regard, the proposed controller tracks the optimal wheel slip ratio with changing the condition of the road surface from dry to wet and icy. The adaptive fuzzy controller consists of linguistic base, inference engine and defuzzifier section. The wheel slip ratio and vehicle longitudinal acceleration are selected as inputs of the controller, controller adapter and detector of the road surface condition. During braking and steering input, effective parameters of the wheel that are affected on the vehicle's dynamic behavior and its stability are investigated.

Design and analysis of output feedback constraint control for antilock braking system based on Burckhardt’s model

PurposeThe purpose of this study is to improve vehicles’ brake stability, the problem of constraint control for an antilock braking system (ABS) with asymmetric slip ratio constraints is concerned. A nonlinear control method based on barrier Lyapunov function (BLF) is proposed not only to track the optimal slip ratio but also to guarantee no violation on slip ratio constraints.Design/methodology/approachA quarter vehicle braking model and Burckhardt’s tire model are considered. The asymmetric BLF is introduced into the controller for solving asymmetric slip ratio constraint problems.FindingsThe proposed controller can implement ABS zero steady-state error tracking of the optimal wheel slip ratio and make slip ratio constraints flexible for various runway surfaces and runway transitions. Simulation and experimental results show that the control scheme can guarantee no violation on slip ratio constraints and avoid self-locking.Originality/valueThe slip rate equation with uncertainties is established, and BLF is introduced into the design process of the constrained controller to realize the slip rate constrained control.

Development of an Antilock Brake System for Electric Vehicles Without Wheel Slip and Road Friction Information

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.

A second-order slip model for constraint backstepping control of antilock braking system based on Burckhardt’s model

ABSTRACTThis paper is concerned with the problem of constraint control for an Antilock Braking System (ABS) with asymmetric slip ratio constraints. A nonlinear backstepping control method based on Barrier Lyapunov Function (BLF) is proposed not only to track the optimal slip ratio but also to guarantee no violation on the slip ratio constraints. A second order slip rate model is established based on a quarter vehicle braking model and a Burckhardt’s tire model. The Asymmetric Barrier Lyapunov Function (ABLF) is introduced into the backstepping controller for solving the asymmetric slip ratio constraint problems. The proposed controller can implement ABS zero steady state error tracking of the optimal wheel slip ratio and make slip ratio constraints flexible for various runway surfaces and runway transitions. Simulation results show that the control scheme can guarantee no violation on slip ratio constraints and avoid self-locking.

Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle

Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a novel model predictive controller-based multi-model control system (MPC-MMCS) is proposed to solve the longitudinal stability problem of DDEV. Firstly, the operation state of DDEV is summarized as three kinds of typical operating modes. A submodel set is established to accurately represent the state value of the corresponding operating mode. Secondly, the matching degree between the state of actual DDEV and each submodel is analyzed. The matching degree is expressed as the weight coefficient and calculated by a modified recursive Bayes theorem. Thirdly, a nonlinear MPC is designed to achieve the optimal wheel slip ratio for each submodel. The optimal design of MPC is realized by parallel chaos optimization algorithm(PCOA)with computational accuracy and efficiency. Finally, the control output of MPC-MMCS is computed by the weighted output of each MPC to achieve smooth switching between operating modes. The proposed MPC-MMCS is evaluated on eight degrees of freedom(8DOF)DDEV model simulation platform and simulation results of different condition show the benefits of the proposed control system.

Optimal Operation Point Detection Based on Force Transmitting Behavior for Wheel Slip Prevention of Electric Vehicles

The optimal wheel slip prevention control of ground vehicles aims at maintaining the operation point around the optimal one to achieve the maximum adhesion utilization, which contributes not only to ensure the adhesion stability but also to obtain the optimal traction performance, particularly being useful for the low grip conditions. However, the uncertainty of tire–road contacts brings great challenges for the optimal operation point determination. This paper proposes a novel methodology for the online search of the optimal operation point under uncertain low grip conditions. First, the force transmitting behavior is analyzed in the stable adhesion state and the unstable slipping state. Then, a determination law to identify the optimal operation point via investigating the adhesion force is proposed, which functions during the transient process from the stable region to the unstable region under the action of an increasing drive force. The adhesion force is estimated using the wheel rotational speed and the wheel drive torque. Both the simulation and experimental results verify the effectiveness of the proposed methodology.

An Integrated Cooperative Antilock Braking Control of Regenerative and Mechanical System for a Hybrid Electric Vehicle Based on Intelligent Tire

AbstractWith the development of the global automotive industry, environmental pollution and driving safety have been major problems. This paper focuses on a novel integrated cooperative antilock braking system (ABS) controller, which is used for antilock regenerative braking systems (ARBS) and antilock mechanical braking systems (AMBS) for hybrid electric vehicles (HEV) driving on different road surfaces. An intelligent tire system is utilized to detect varying road surfaces to obtain friction information and optimal operation slip ratio. In addition, the HEV eight‐degree‐of‐freedom dynamics model is developed for ABS control, which includes the LuGre tire model. Adaptive backstepping and finite state machine controllers are explored to maintain optimal wheel slip and regenerate energy, based on wheel slip, battery state of charge (SOC), motor capability torque, and vehicle velocity, and to develop the switching rules of regenerative and mechanical braking systems. In order to evaluate the performance of regenerative and mechanical braking systems on harvesting energy and driving safety, the HEV and LuGre dynamic tire models are developed in MATLAB SIMULINK /SimDriveline. The estimation results of different road surfaces and slip controller effects are tested via the experiments and simulations, finding good braking performances and high regenerative efficiency in different maneuvers.

A Dynamic Method to Forecast the Wheel Slip for Antilock Braking System and Its Experimental Evaluation

The control of an antilock braking system (ABS) is a difficult problem due to its strongly nonlinear and uncertain characteristics. To overcome this difficulty, the integration of gray-system theory and sliding-mode control is proposed in this paper. This way, the prediction capabilities of the former and the robustness of the latter are combined to regulate optimal wheel slip depending on the vehicle forward velocity. The design approach described is novel, considering that a point, rather than a line, is used as the sliding control surface. The control algorithm is derived and subsequently tested on a quarter vehicle model. Encouraged by the simulation results indicating the ability to overcome the stated difficulties with fast convergence, experimental results are carried out on a laboratory setup. The results presented indicate the potential of the approach in handling difficult real-time control problems.

A performance evaluation of an automotive magnetorheological brake design with a sliding mode controller

The aim of this work is to develop a magnetorheological brake (MRB) system that has performance advantages over the conventional hydraulic brake system. The proposed brake system consists of rotating disks immersed in a MR fluid and enclosed in an electromagnet, which the yield stress of the fluid varies as a function of the magnetic field applied by the electromagnet. The controllable yield stress causes friction on the rotating disk surfaces, thus generating a retarding brake torque. The braking torque can be precisely controlled by changing the current applied to the electromagnet. In this paper, an optimum MRB design with two rotating disks is proposed based on a design optimization procedure using simulated annealing combined with finite element simulations involving magnetostatic, fluid flow and heat transfer analysis. The performance of the MRB in a vehicle was studied using a quarter vehicle model. A sliding mode controller was designed for an optimal wheel slip control, and the control simulation results show fast anti-lock braking.