Doppler-Based Ground Speed Sensor Fusion and Slip Control for a Wheeled Rover

High-speed unmanned ground vehicles evolving on natural terrains can exhibit a significant slip and skid. An estimation of both friction and traction forces can allow to achieve a better control. In order to implement a control architecture based on the vehicle dynamic model and the wheel–soil interaction model, the knowledge of the wheels slip rate is required. The wheel angular velocities can be precisely measured. But the true measurement of the ground speed of the vehicle is much more challenging. A low-cost Doppler radar is used, in conjunction with an accelerometer, to obtain the ground speed. Thus, the knowledge of the slip rate allows us to setup an in situ procedure for the estimation of soil parameters that is based on the measurement of the motors torques. A wheel slippage controller has also been implemented, which is a first step toward high-level dynamic control.      

Longitudinal wheel slip control using dynamic neural networks

The control of automotive braking systems performance and a wheel slip is a challenging problem due to nonlinear dynamics of a braking process and a tire–road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire–road friction force cannot be achieved, which influences braking distance, the loss in steerability and maneuverability of the vehicle. In this paper, the new approach, based on dynamic neural networks, has been employed for improving of the longitudinal wheel slip control. This approach is based on dynamic adaptation of the brake actuation pressure, during a braking cycle, according to the identified maximum adhesion coefficient between the wheel and road. The brake actuated pressure was adjusted on the level which provides the optimal longitudinal wheel slip versus the brake actuated pressure selected by a driver, the current vehicle speed, load conditions, the brake interface temperature and the current value of the wheel slip. The dynamic neural network has been used for modeling of a nonlinear functional relationship between the brake actuation pressure and the longitudinal wheel slip during a braking cycle. It provided preconditions for control of the brake actuation pressure based on the wheel slip change.     

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

This paper presents a new slip control system for electric vehicles (EVs) equipped with four in-wheel motors, based on nonlinear model predictive control (nonlinear MPC) scheme. In order to ensure vehicle safety, wheel slip stable zone is considered as time-domain constraints of the nonlinear MPC. Besides, the motor output torque is limited by the motor maximum torque, which varies with motor angular velocity and battery voltage, so the motor maximum output torque limitation is considered as system time-varying constraints. The control objectives include: vehicle safety, good longitudinal acceleration and braking performance, preservation of driver comfort and lower power consumption. This paper utilizes nonlinear MPC to solve this complex optimization control problem subject to the constraints, and the vehicle safety objective is achieved by wheel slip stable zone constraints, the other objectives are realized by adding additional cost functions. In addition, a penalty on the slack variables is also added to ensure that the state constraints (wheel slip) do not cause infeasible problems. The effectiveness of the proposed controller is verified in the off-line co-simulation environment of AMESim and Simulink, and a rapid control prototyping platform based on Field programmable gate array (FPGA) and dSPACE is completed to evaluate the real time functionality and computational performance of the nonlinear MPC controller.     

Real-time slip-based estimation of maximum tire-road friction coefficient

This paper presents a real-time maximum tire-road friction coefficient estimation method and field test results. The estimator is based on the relationship between the wheel slip ratio and the friction coefficient. An effective tire radius observer and a tire normal force observer have been designed for the computation of the slip ratio from wheel speed and vehicle speed measurements. The effective tire radius observer has been used so that the proposed method works for all driving situations. A tractive force estimator, a brake gain estimator, and a normal force observer have been used for the estimation of the friction coefficient. The proposed estimation method for the maximum tire-road friction coefficient has been implemented using a fifth wheel and typical vehicle sensors such as engine speed, carrier speed, throttle position, and brake pressure sensors.     

Compensation of axle-generator errors due to wheel slip and slide

Significant errors of train axle generators (tachometers) are due to wheel slip and slide. An algorithm is designed to compensate for these errors. The algorithm identifies the wheel slip and slide by examining the variation of the processed vehicle longitudinal acceleration. Whenever wheel slip/slide is identified, then the vehicle speed is adjusted if a certain condition is met. The adjustment is a simple linear interpolation between the two speed values recorded before and after wheel slip/slide detection. In addition, a speed and acceleration observer using a Kalman filter is implemented. Experimental results using three different axle encoders aboard a freight train are provided to illustrate the performance of the proposed algorithm     

Design of an Optimal Fuzzy Controller for Antilock Braking Systems

Antilock braking systems (ABSs) have been developed to improve vehicle control during sudden braking, especially on slippery road surfaces. The objective of such control is to increase wheel traction force in the desired direction while maintaining adequate vehicle stability and steerability and reducing the vehicle stopping distance. In this paper, an optimized fuzzy controller is proposed for ABSs. The objective function is defined to maintain the wheel slip to a desired level so that maximum wheel traction force and maximum vehicle deceleration are obtained. All the components of a fuzzy system are optimized using genetic algorithms. The error-based global optimization approach is used for fast convergence near the optimum point. Simulation results show fast convergence and good performance of the controller for different road conditions     

Adaptive vehicle skid control

In this paper, adaptive vehicle skid control, for stability and tracking of a vehicle during slippage of its wheels without braking, is addressed. Two adaptive control algorithms are developed: one for the case when no road condition information is available, and one for the case when certain information is known only about the instant type of road surface on which the vehicle is moving. The vehicle control system with an adaptive control law keeps the speed of the vehicle as desired by applying more power to the drive wheels where the additional driving force at the non-skidding wheel will compensate for the loss of the driving force at the skidding wheel, and also arranges the direction of the vehicle motion by changing the steering angle of the two front steering wheels. Stability analysis proves that the vehicle position and velocity errors are both bounded. With additional road surface information available, the adaptive control system guarantees that the vehicle position error and velocity error converge to zero asymptotically even if the road surface parameters are unknown.     

A new strategy for traction control in turning via engine modeling

The driving stability is affected by driven wheel slip, which can be controlled by the driven wheel torque. In a vehicle powered by an internal combustion engine, the torque can be controlled by an engine management system. The sliding mode algorithm is the mechanism behind the design of the traction control system (TCS). The longitudinal slip is controlled by the position of the throttle valve. The vehicle model used has seven degrees of freedom and a two-state engine model, i.e., the mass of air in the intake manifold and the engine speed. Time-delay transport is considered in the engine model used. A nonlinear tire model for combined slip is used for tire force computation. Due to the nonlinear dynamic of the tire, vehicle, and engine, the control method of sliding mode is used for its robustness. A controller is designed based on the dynamic surface control, for which two first-order surfaces are defined. The effectiveness of the controller is demonstrated with simulation results for different maneuvers. Results show that for different road conditions, the acceleration performance, directional stability, and steerability of a vehicle equipped with TCS is improved. The reason is that the slip is controlled by keeping it in a desired range     

Prediction of cellular characteristics for various urbanenvironments

The propagation channel for UHF/X-band waves in the city is modeled for two typical cases in the urban scene: (a) by regularly distributed rows of buildings placed on a flat terrain; and (b) by an array of randomly distributed buildings placed on rough terrain. The law of distribution of buildings in both cases is assumed to be Poisson. The loss characteristics in such urban propagation channels, as well as the co-channel interference parameter, the carrier-to-interference ratio (C/I), are investigated. In case (a), the three-dimensional multi-slit waveguide model is used for LOS conditions, and the two-dimensional multi-diffraction model is used for NLOS conditions. In case (b), the statistical parametric model of wave propagation is used, including single and multiple scattering effects, diffraction from buildings' roofs, the actual built-up relief, and various positions of receiver and transmitter antennas on rough terrain. The full algorithm for predicting propagation and cellular characteristics to increase the accuracy of radio and cellular maps is presented     

Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

This paper presents system modeling, analysis, and simulation of an electric vehicle (EV) with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability when there are no differential gears. Using two in-wheel electric motors makes it possible to have torque and speed control in each wheel. This control level improves EV stability and safety. The proposed traction control system uses the vehicle speed, which is different from wheel speed characterized by a slip in the driving mode, as an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. The analysis and simulations lead to the conclusion that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily.     

加减速过程中车载航位推算误差补偿技术研究

研究轮式车辆加减速过程中带来的两种效应,即车辆载荷的转移及轮胎的滑动,并分析其对车辆航位推算的影响,综合这两种效应带来的影响,提出了轮胎计算半径的概念,建立了加减速过程中的误差补偿模型.跑车实验表明,经过误差补偿距离精度由3‰提高到0.5‰,精度提高近1个数量级.     

基于单线激光雷达的目标车辆位姿检测方法

对目标车辆的信息进行高效、准确的检测是自动泊车、智能交通等领域的关键技术之一。针对智能泊车机器人对目标车辆进行近距离测量的需求,提出了一种基于单线激光雷达的车辆位姿检测方法。利用激光雷达扫描目标车辆底部区域,并使用DBSCAN聚类算法分割点云。将车轮点云簇视作L形特征,提出了一种基于特征点搜索的车轮拟合算法,同时给出了两种特征角点搜索准则。针对获取的车轮集合,提出了一种筛选目标车辆车轮的策略,假定了两种车辆位姿检测工况并设计了对应的算法。通过实车环境下的测试,验证了方法的实时性、准确性,满足了泊车机器人的位姿检测需求。     

SEKE: A computer model for low altitude radar propagation over irregular terrain

SEKE, a new site-specific propagation model for general terrain, makes use of the original Lincoln Laboratory models geometrical optics (GOPT), low altitude propagation spherical earth (LAPSE), and low altitude propagation knife edges (LAPKE) to compute multipath, spherical earth diffraction, and multiple knife-edge diffraction losses. The proper algorithm is selected based on terrain geometry, antenna and target heights, and frequency. Comparison of model predictions with measurements over several paths ranging from level to rough at five frequencies (X-band through VHF) is presented. A brief discussion on the performance of SEKE over general terrain with respect to the expected performance of the two other general terrain-specific models (Longley-Rice and terrain integrated rough earth model (TIREM)) is given.     

Simplified terrain identification and component fatigue damage estimation model for use in a health and usage monitoring system

Improved reliability of military ground vehicle systems is often in direct conflict with increased functionality and performance. Health and Usage Monitoring Systems or HUMS are being developed to address this issue. Traditionally, HUMS applications have been limited to high-cost equipment such as aircraft. In order to apply a HUMS to a relatively inexpensive military ground vehicle, simplified algorithms that derive terrain exposure from a basic set of sensors and estimate fatigue damage accumulated on components whose loading comes primarily from terrain have been developed. Various inputs and statistical parameters are evaluated for this model based on accuracy of terrain identification and quality of fatigue prediction on an example component. The generalized process and recommendations for application of this model to military ground vehicle systems are discussed.     

基于视频的车辆检测与跟踪算法综述

首先介绍了交通检测系统,指出视频交通检测技术日益成为计算机视觉领域中备受关注的前沿方向。在此基础上,分别讨论了常用的车辆检测算法,基于模型的车辆检测算法,车辆跟踪的基本类型,以及基于模板匹配、卡尔曼滤波和粒子滤波的车辆跟踪算法,同时分析比较了各种算法的优缺点。最后,展望了这一领域未来研究的热点。     

相位编码雷达高度表中宽带多普勒信号的检测

安装在高速运动载体上的雷达高度表,其地面回波被一宽带多普勒信号所调制。相位编码雷达可以采用一种检测方法实现对该宽带多普勒信号的检测,其结果不但可以指示速度,而且还可以作为速度选通的抗干扰措施。针对一种面目标,在视频上通过仿真手段研究了该检测方法在加噪和不加噪两种情况下的检测结果。     

Adaptive Vehicle Lateral-Plane Motion Control Using Optimal Tire Friction Forces With Saturation Limits Consideration

This paper presents an adaptive nonlinear control scheme aimed at the improvement of the handling properties of vehicles. The control inputs for steering intervention are the steering angle and wheel torque for each wheel, i.e., two control inputs for each wheel. The control laws are obtained from a nonlinear 7-degree-of-freedom (DOF) vehicle model. A main loop and eight cascade loops are the basic components of the integrated control system. In the main loop, tire friction forces are manipulated with the aim of canceling the nonlinearities in a way that the error dynamics of the feedback linearized system has sufficient degrees of exponential stability; meanwhile, the saturation limits of tires and the bandwidth of the actuators in the inner loops are taken into account. A modified inverse tire model is constructed to transform the desired tire friction forces to the desired wheel slip and sideslip angle. In the next step, these desired values, which are considered as setpoints, are tackled through the use of the inner loops with guaranteed tracking performance. The vehicle mass and mass moment of inertia, as unknown parameters, are estimated through parameter adaptation laws. The stability and error convergence of the integrated control system in the presence of the uncertain parameters, which is a very essential feature for the active safety means, is guaranteed by utilizing a Lyapunov function. Computer simulations, using a nonlinear 14-DOF vehicle model, are provided to demonstrate the desired tracking performance of the proposed control approach.     

Vertically aligned accelerometer for wheeled vehicle odometry

A new application for accelerometers is presented and evaluated instead of using it to measure the linear acceleration of the vehicle, which is usually performed with traditional odometry. In the present case, a dual orthogonal axis accelerometer is vertically aligned in the center of a wheel. Then the rotational position of the wheel can be detected and RPM can be counted based on the accelerometer angular position. A microcontroller is used to measure the value of each accelerometer axis, and with a proper algorithm 12 wheel positions are detected combining the x-axis and y-axis values. The wheel position is transmitted by means of a wireless link to another microcontroller or computer located on board of the vehicle to estimate the traveled distance. This embedded wireless device is now named accelodometer. Field results on a pick-up tested at up to 40 km/h and with an autonomous robotic vehicle showed that this accelodometer presented advantages with respect to both usual accelerometer and incremental encoder, avoiding the accumulative error due to the sensor drift.The repeatability of the device was established within the 0.01% in 4 km path. A resolution of 1/12 of the wheel perimeter was determined.     

Nonconventional three-wheel electric vehicle for urban mobility

This paper outlines the original solutions adopted for powering a nonconventional three-wheel electric vehicle. This is a lightweight vehicle for use in urban mobility with mission tasks such as 50 km/h cruising speed and 80 km range of autonomy. The propulsion system is based on a lead-acid battery-fed wheel direct drive. This is arranged with a 4.5 kW prototype of a slotless axial-flux permanent magnet machine, which has a total weight of 15 kg and is capable of 85 Nm continuous torque and 120 Nm peak torque over 2 min. The motor is totally enclosed in the single front wheel of the vehicle and fed through an IGBT bidirectional power converter, which allows the control of both motoring and regenerative braking operations. Design characteristics and experimental data taken from the prototype of wheel direct drive are given     

A novel driver assist stability system for all-wheel-drive electric vehicles

A novel driver-assist stability system for all-wheel-drive electric vehicles is introduced. The system helps drivers maintain control in the event of a driving emergency, including heavy braking or obstacle avoidance. The system comprises a fuzzy logic system that independently controls wheel torque to prevent vehicle spin. Another fuzzy wheel slip controller is used to enhance vehicle stability and safety. A neural network is trained to generate the required reference for yaw rate. Vehicle true speed is estimated by a sensor data fusion method. The intrinsic robustness of fuzzy controllers allows the system to operate in different road conditions successfully. Moreover, the ease of implementing fuzzy controllers gives a potential for vehicle stability enhancement.