Excessive Wheel Slip Research Articles

Совершенствование системы защиты от юза пассажирского электровоза

Objective: improving algorithms for protection against skidding and slipping using new methods for detecting excessive slipping of locomotive wheel pairs, allowing for early detection of the moment of loss of adhesion. Methods: the effectiveness of an anti-skid system is largely determined by the reliable detection of the occurrence of excessive wheel slip. Solving this problem requires the development of methods for isolating signals from the angular velocity of rotation and angular acceleration of the wheelset, taking into account dynamic processes in the mechanical part of the locomotive and interference in the measurement channel. Therefore, the article discusses the issues of processing rotation speed signals, extracting information about the amount of excess slip and angular acceleration of the wheelsets for use in anti-skid and skidding systems. One of the criteria that can improve the reliability of skid detection is proposed to use the “Estimated time before wheel locking”. Its value allows you to define the estimated time before the wheel jams (stops rotation). The introduction of this criterion makes it possible to more accurately determine the risk of a complete stop of wheelset rotation and increases the reliability of determining the occurrence of skidding. Results: it has been established that to eliminate errors in the measurement channel and isolate the signal about the angular acceleration of the wheelset in conditions of the presence of oscillations caused by the presence of the effects of the spatial dynamics of the locomotive, it is advisable to use a discrete Kalman filter. Signal processing using a Kalman filter in the presence of a reference signal makes it possible to significantly reduce the influence of spatial vibrations of the undercarriage of an electric locomotive when moving along a track with irregularities on the extracted signals of the angular velocity of rotation and angular acceleration of the wheelset. This makes it possible to reduce response thresholds and identify skidding and skidding before significant excess slip occurs. Practical importance: the necessity of using complex criteria based on the analysis of not only the slipping speed of wheelsets, but also angular accelerations, is shown to identify excessive slipping of locomotive wheelsets. Their use in the locomotive control system makes it possible to detect loss of adhesion in the early stages of slipping and skidding and improve the use of the adhesion weight of locomotives

Optimal Control Design for Decoupling the Direct Drive Stability of Distributed Drive Electric Vehicles

As a new type of drive for electric vehicles, distributed drive has many advantages such as simple structure and easy control, and is one of the important development directions of new energy vehicles in the future. In the past decade, the research on the active safety control of distributed drive electric vehicles has become more and more mature. In this paper, we propose a decoupled optimal control strategy based on the drive torque for the vehicle run-off and motion coupling problems that exist during the straight-line driving of distributed-drive electric vehicles. The upper control logic layer is responsible for cross-swing motion control and drive anti-skid control. The middle control logic layer is responsible for secondary planning of the additional torque from the upper control layer, based on which the decoupled cross-swing motion control with wheel anti-skid is realised. The lower control logic layer is responsible for the optimal distribution of the drive torque for speed following control. The decoupled optimal control of drive torque proposed in this paper can achieve the optimal distribution of drive torque, avoiding vehicle deflection on the premise of ensuring vehicle speed, while preventing excessive wheel slip, realising the decoupled control of vehicle linear motion and enhancing the linear driving stability of the vehicle.

A joint control method considering travel speed and slip for reducing energy consumption of rear wheel independent drive electric tractor in ploughing

Improving tractor traction efficiency is greatly important in increasing energy efficiency and reducing fossil fuel consumption. However, the wheeled tractors have problems with low traction energy efficiency and severe energy consumption due to excessive wheel slip in ploughing. This paper proposed a joint control method considering the travel speed and slip based on the active torque distribution, which is applied to the independent drive electric tractors. Considering the influence factors of time-varying resistance and terrain elevation in ploughing, a time-varying dynamical model for the tractor-implement combination was established to reveal the load transfer rules. Then the optimal slip values of the driving wheels were solved in real-time, and a sliding mode algorithm was used to control the motor torque for efficient tractor operation. Moreover, a hardware-in-the-loop platform was built, and ploughing tests were performed. The results indicated that the tractor slip, traction energy efficiency and motor energy consumption of the tractor were optimal in the torque active distribution mode. Compared to the torque average distribution mode, the proposed method reduced the tractor slip by 14.1%, the motor energy consumption by 6.8% and increased the traction energy efficiency by 6.8%. This study provided technical support for reducing energy dissipation in ploughing.

Predict the Rover Mobility Over Soft Terrain Using Articulated Wheeled Bevameter

Robot mobility is critical for mission success, especially in soft or deformable terrains, where the complex wheel-soil interaction mechanics often leads to excessive wheel slip and sinkage, causing the eventual mission failure. To improve the success rate, online mobility prediction using vision, infrared imaging, or model-based stochastic methods have been used in the literature. This paper proposes an on-board mobility prediction approach using an articulated wheeled bevameter that consists of a force-controlled arm and an instrumented bevameter (with force and vision sensors) as its end-effector. The proposed bevameter, which emulates the traditional terramechanics tests such as pressure-sinkage and shear experiments, can measure contact parameters ahead of the rover's body in real-time, and predict the slip and sinkage of supporting wheels over the probed region. Based on the predicted mobility, the rover can select a safer path in order to avoid dangerous regions such as those covered with quicksand. Compared to the literature, our proposed method can avoid the complicated terramechanics modeling and time-consuming stochastic prediction; it can also mitigate the inaccuracy issues arising in non-contact vision-based methods. We also conduct multiple experiments to validate the proposed approach.

Travel Reduction Control of Distributed Drive Electric Agricultural Vehicles Based on Multi-Information Fusion

In agricultural vehicles with internal combustion engines, owing to the use of rear-wheel drive or four-wheel drive, it is difficult to obtain information regarding the slip of the driving wheels. Excessive wheel slip, an inevitable phenomenon occurring during agricultural activities, can easily damage the original soil surface and result in excessive energy consumption. To solve these problems, a distributed drive agricultural vehicle (DDAV) based on multi-information fusion was proposed. The actual travel reduction of each wheel was calculated by determining the vehicle parameters in order to deliver the required torque to the four drive wheels via sliding mode control (SMC) and incremental proportional-integral (PI) control. Through this process, the vehicle always operates in a straight line. Test results show that, on a uniform surface, the travel reduction of each wheel can be maintained at the target value by using the incremental PI control strategy, with only minor fluctuations, to make the vehicle run in a straight line (R2 = 0.9999). Furthermore, on a separated surface, the travel reduction of each wheel can be maintained at the target value, and using the SMC strategy enables more identical coefficient of gross tractions for each wheel to make the vehicle run in a straight line (R2 = 0.9902). Unlike the non-control strategy, the vehicle reaches a stable state within 1 s, owing to the use of a controller that can effectively reduce the impact of road changes on vehicle velocity. This study can provide a reference for the drive control of DDAVs.

All-Wheel-Drive Torque Distribution Strategy for Electric Vehicle Optimal Efficiency Considering Tire Slip

The existing energy management strategies for four-wheel-drive electric vehicles only take into account the vehicle energy consumption under static adhesion constraints. However, the front and rear axle loads transfer under dynamic conditions lead to the variations of vehicle adhesion characteristics, which results in the changes of vehicle energy consumptions. In this paper, a multi-objective optimal torque distribution strategy is proposed, taking into account the front and rear axle load transfer and the variations of adhesion characteristics. The advantages of the proposed strategy are verified through simulation studies in terms of vehicle energy consumption and wheel slip ratio, in comparison with the average torque distribution strategy and the optimal torque distribution strategy based on Sequential Quadratic Programming Algorithm. The simulation results show that the economy performance of the proposed strategy is superior to those of the competing methods. Furthermore, the proposed strategy provides good power performance and eliminates excessive wheel slip, which in turn ensures vehicle longitudinal stability and avoids energy loss resulting from frequent ASR interventions.

Validation of an anti-slip control method based on the angular acceleration of a wheel on a roller rig

This study deals with the validation of an anti-slip control method that is based on the acceleration of a wheel. The method uses the angular acceleration signal and a threshold value to prevent the wheel from a severe slip. Initially, the implemented method was tested with an experimental roller rig under several wheel–roller surface conditions (half-dry, wet and greasy). Then, the validity of the control algorithm was verified using the numerical model of a full-scale roller rig that is built via the MATLAB editor, with the simulation scenarios following the experiments. The results from both experiments and simulations confirm that the acceleration-based slip regulation controller prevents the excessive wheel slip and improves the traction performance of a rail vehicle. Moreover, it is observed that the performance of the controller could be further improved by properly setting the control parameters of the acceleration-based slip regulation controller.

Near real-time monitor of rail way track adhesion conditions

In this paper we examine the possibilities of using sensor data from trains in service to develop a real-time monitor of the adhesion conditions of the rail. In everyday railway operations, low adhesion conditions of the track are an important challenge for railway operators, since these may result in a loss of punctuality, an increase in wear of both wheel and rail, and in an increase of the risk for red signal passage in situations where trains are unable to stop in time. At the same time, prudent driving behavior while the adhesion conditions returned to normal, results in unnecessary train delays. A central issue here is that rail adhesion conditions vary across space and time. To date it is a challenge to give accurate real-time information to both train drivers and infrastructure managers. With real-time monitoring of the adhesion conditions, the drivers can adjust their (de)acceleration control to local adhesion conditions and thereby minimize wear, and the infrastructure managers could improve the track conditions by taking friction enhancing measures. To monitor the adhesion conditions of the track, we used real-time sensor data from ~20 trains. We designed an algorithm that can diagnose track sections as having either slippery or normal adhesion conditions. Specifically, we trained a logistic classifier on a data set that contained reported rail adhesion conditions as well as sensor data from trains in service, such as information about traction, velocity, excessive wheel slip-/sliding detection, and weight. We then assessed the performance of this classifier using an independent test data set. This first assessment shows a classification accuracy of approximately 77%, with a ~23% false positive rate and a ~23% false negative rate, when compared to the drivers reporting. Several improvements are proposed to increase the sensitivity, which outline the directions of our future research towards the implementation of a real-time monitor of railway track adhesion conditions.

Novel coordinated algorithm for Traction Control System on split friction and slope road

A Traction Control System (TCS) is used to avoid excessive wheel-slip via adjusting active brake pressure and engine torque when vehicle starts fiercely. The split friction and slope of the road are complicated conditions for TCS. Once operated under these conditions, the traction control performance of the vehicle might be deteriorated and the vehicle might lack drive capability or lose lateral stability, if the regulated active brake pressure and engine torque can’t match up promptly and effectively. In order to solve this problem, a novel coordinated algorithm for TCS is brought forward. Firstly, two brake controllers, including a basic controller based on the friction difference between the two drive wheels for compensating this difference and a fuzzy logic controller for assisting the engine torque controller to adjust wheel-slip, are presented for brake control together. And then two engine torque controllers, containing a basic PID controller for wheel-slip control and a fuzzy logic controller for compensating torque needed by the road slope, are built for engine torque control together. Due to the simultaneous and accurate coordination of the two regulated variables the controlled vehicle can start smoothly. The vehicle test and simulation results on various road conditions have testified that the proposed method is effective and robust.

Longitudinal velocity and road slope estimation in hybrid electric vehicles employing early detection of excessive wheel slip

Vehicle speed is one of the important quantities in vehicle dynamics control. Estimation of the slope angle is in turn a necessity for correct dead reckoning from vehicle acceleration. In the present work, estimation of vehicle speed is applied to a hybrid vehicle with an electric motor on the rear axle and a combustion engine on the front axle. The wheel torque information, provided by electric motor, is used to early detect excessive wheel slip and improve the accuracy of the estimate. A best-wheel selection approach is applied as the observation variable of a Kalman filter which reduces the influence of slipping wheels as well as reducing the computational effort. The performance of the proposed algorithm is illustrated on a test data recorded at a winter test ground with excellent results, even for extreme conditions such as when all four wheels are spinning.

Single wheel drives for wheel slip control

Ever-increasing electrification of the drive train offers new possibilities for the power train layouts as well as for vehicle dynamics control. For a single-wheel driven electric vehicle, one should utilize the advantages of the electric engines compared to conventional components. Within this contribution, an optimized arrangement regarding installation space of the drive train with single rear wheel drive was investigated. The electric motors were used for acceleration and deceleration, hence regenerative braking. Often, for brake situations with excessive wheel slip, electric engines are switched off and conventional components as the hydraulic wheel brakes are used to control the wheel speed. A control scheme for a rearwheel driven electric vehicle with single wheel drives is presented, where only the rear engines and no friction brakes are used for all driving and braking torques. The effectiveness of the proposed control scheme has been proven in real vehicle tests for acceleration as well as for braking situations on low friction coefficient surface (snow).

Development of a new traction control system for vehicles with automatic transmissions

A traction control system (TCS) is used to improve the acceleration performance on slippery roads by preventing excessive wheel slip. In this paper, a new traction control system using the integrated control of gear shifting and throttle actuation is developed for vehicles with automatic transmissions. In the design of the slip controller, by means of a differential manifold transformation, a slip control system with nonlinearities and uncertainties is transformed into a linear system, and a sliding mode controller is applied for the purpose of increasing the robustness of the system. Next, to achieve the required driving torque, the optimal throttle and gear position, maps are constructed based on dynamic programming. The simulation results indicate that the present traction control system can improve the acceleration performance of an automatic transmission vehicle for various types of road conditions.

A new concept traction control for F-1 racing car

A traction control had been applied to a racing car of Formula One (F-1) from 2001 to 2007. General traction controls had used feedback algorithms based on the wheel slip of driving wheels. However, general traction controls cannot reduce engine torque before wheel slip occurs. This lag characteristic of the general traction controls rarely causes excessive wheel slip. When excessive wheel slip occurs, the yaw behaviour of the racing car become unsuitable and the vehicle speed during going around a turn becomes slow. Therefore, a new traction control composed of an adaptive feedforward function and a feedback function was designed to improve the stability of vehicle behaviour. The adaptive feedforward function automatically updates a torque limit value on the basis of reduction behaviour of engine torque controlled by the feedback function, and restricts driver’s demanded engine torque to the torque limit value before wheel slip occurs.

각가속도 변화에 의해 탐지된 슬립에 기반한 주행로봇의 견인력 제어

The common requirements of rough terrain mobile robots are long-term operation and high mobility in rough terrain to perform difficult tasks. In rough terrain, excessive wheel slip could cause an increase in the amount of dissipated energy at the contact point between the wheel and ground or, even more seriously, the robot could lose all mobility and become trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The proposed traction algorithm is analogous to the stick-slip friction mechanism. The algorithm estimates the slippage of wheels by angular acceleration change, and controls the increase or decrease state of torque applied to wheels Simulations are performed to validate the algorithm. The proposed traction control algorithm yielded a 65.4% reduction of total slip distance and 70.6% reduction of power consumption compared with the standard velocity control method.

Independent traction control for uneven terrain using stick-slip phenomenon: application to a stair climbing robot

Mobile robots are being developed for building inspection and security, military reconnaissance, and planetary exploration. In such applications, the robot is expected to encounter rough terrain. In rough terrain, it is important for mobile robots to maintain adequate traction as excessive wheel slip causes the robot to lose mobility or even be trapped. This paper proposes a traction control algorithm that can be independently implemented to each wheel without requiring extra sensors and devices compared with standard velocity control methods. The algorithm estimates the stick-slip of the wheels based on estimation of angular acceleration. Thus, the traction force induced by torque of wheel converses between the maximum static friction and kinetic friction. Simulations and experiments are performed to validate the algorithm. The proposed traction control algorithm yielded a 40.5% reduction of total slip distance and 25.6% reduction of power consumption compared with the standard velocity control method. Furthermore, the algorithm does not require a complex wheel-soil interaction model or optimization of robot kinematics.