Nonlinear tire-road friction control based on tire model parameter identification

A hierarchical control structure is a more suitable structural scheme for integrated chassis control. Generally, this type of structure has two main functions. The upper layer manages global control and force allocation, while the bottom layer allocates realized forces with 4 independent local tire controllers. The way to properly allocate these target forces poses a difficult task for the bottom layer. There are two key problems that require attention: obtaining the nonlinear time-varying coefficient of friction between the tire and different road surfaces and accurately tracking the desired forces from the upper layer. This paper mainly focuses on longitudinal tire-road friction allocation and control strategies that are based on the antilock braking system (ABS). Although it is difficult to precisely measure longitudinal tire-road friction forces for frequently changing road surface conditions, they can be estimated with a real-time measurement of brake force and angular acceleration at the wheels. The Magic Formula model is proposed as the reference model, and its key parameters are identified online using a constrained hybrid genetic algorithm to describe the evolution of tire-road friction with respect to the wheel slip. The desired wheel slip, with respect to the reference tire-road friction force from the top layer, is estimated with the inverse quadratic interpolation method. The tire-road friction controller of the extended anti-lock braking system (Ext-ABS) is designed through use of the nonlinear sliding mode control method. Simulation results indicate that acceptable modifications to changes in road surface conditions and adequate stability can be expected from the proposed control strategy.     

Direct tire force generation algorithm based on non-iterative nonlinear inverse tire model

The function of vehicle dynamics control system is adjusting the yaw moment, the longitudinal force and lateral force of a vehicle body through several chassis systems, such as brakes, steering and suspension. Individual systems such as ESC, AFS and 4WD can be used to achieve desired performance by controlling actuator variables. However, integrated chassis control systems that have multiple objectives may not simply achieve the desired performance by controlling the actuators directly. Usually those systems determine the required tire forces in an upper level controller and a lower level controller regulates the tire forces through the actuators. The tire force is controlled in a recursive way based on vehicle state measurement, which may not be sufficient for fast response. For immediate force tracking, we introduce a direct tire force generation method that uses a nonlinear inverse tire model, a pseudo-inverse model of vehicle dynamics and the relationship between longitudinal force and brake pressure.     

Sensitivity analysis of side-slip angle observer based on a tire model

We investigated the sensitivity of an observer based on a tire model using simulation in linear and nonlinear regions. In the linear region, we investigated the influence of vehicle speed by doing the same simulation at three speed levels. In the nonlinear region, the simulation condition was set such that the vehicle became unstable. In the linear region, steering input and cornering stiffness have a relatively large effect on the estimation error because these quantities determine tire side force. In the nonlinear region, the road surface’s friction coefficient becomes a crucial factor. In both the regions, the observer is sensitive to yaw rate and longitudinal speed.     

Sensitivity analysis of side-slip angle observer based on a tire model

We investigated the sensitivity of an observer based on a tire model using simulation in linear and nonlinear regions. In the linear region, we investigated the influence of vehicle speed by doing the same simulation at three speed levels. In the nonlinear region, the simulation condition was set such that the vehicle became unstable. In the linear region, steering input and cornering stiffness have a relatively large effect on the estimation error because these quantities determine tire side force. In the nonlinear region, the road surface's friction coefficient becomes a crucial factor. In both the regions, the observer is sensitive to yaw rate and longitudinal speed.     

Analysis of an automotive ground system based on its steady-state model

As more electrical equipment is installed and larger currents are required in vehicles, the automotive ground system becomes more important to guarantee the stable operation of the equipment and efficient power consumption. In this paper, an automotive ground system is analyzed in a steady-state condition, and a simulation model for estimating its ground voltage distribution is described. The automotive ground system is divided into an engine compartment ground and a body ground, and it is modeled as an equivalent resistor network, which is suitable for simulation. By using the developed model, ground voltages are simulated and measurements are taken with a real car. A comparison of the simulation and measurement results shows good agreement, and the validity of the model is confirmed. Then, the factors that dominate the ground voltage level are discussed.     

A semi-empirical dynamic tire model for combined-slip forces

This article presents a semi-empirical combined-slip tire model including transient behavior. It is assumed that the transient behavior is a result from the dynamic deformation of the tire carcass and that the interaction between the lateral and longitudinal slip, and forces can be explained by the deformation of the rubber treads. The deformation of the tire carcass makes the tread slip deviate from the wheel-rim motion in a way that may be described by differential equations. A method based on brush-model tire mechanics is used to construct the combined-slip forces as nonlinear scalings of corresponding pure-slip forces.     

A two-dimensional tire model on uneven roads for vehicle dynamic simulation1

This study proposes a comprehensive analytical tire model for handling and ride comfort in low frequency ranges. A contact algorithm that is developed in this study provides a two-dimensional contact pressure distribution on even and uneven road surfaces with reasonable computational cost. Shear stresses and strains during cornering and braking are estimated by direct measurement of tread deformations. The model is validated against experimental force and moment data for general handling simulations. Cleat tests are also conducted and validated under different forward velocity and vertical load conditions for a tire vibration study.     

Quasi steady-state aerodynamic model development for race vehicle simulations

Presented in this paper is a procedure to develop a high fidelity quasi steady-state aerodynamic model for use in race car vehicle dynamic simulations. Developed to fit quasi steady-state wind tunnel data, the aerodynamic model is regressed against three independent variables: front ground clearance, rear ride height, and yaw angle. An initial dual range model is presented and then further refined to reduce the model complexity while maintaining a high level of predictive accuracy. The model complexity reduction decreases the required amount of wind tunnel data thereby reducing wind tunnel testing time and cost. The quasi steady-state aerodynamic model for the pitch moment degree of freedom is systematically developed in this paper. This same procedure can be extended to the other five aerodynamic degrees of freedom to develop a complete six degree of freedom quasi steady-state aerodynamic model for any vehicle.     

A simplified model for evaluating tire wear during conceptual design

In the field of vehicle dynamics, commercial software can aid the designer during the conceptual and detailed design phases. Simulations using these tools can quickly provide specific design metrics, such as yaw and lateral velocity, for standard maneuvers. However, it remains challenging to correlate these metrics with empirical quantities that depend on many external parameters and design specifications. This scenario is the case with tire wear, which depends on the frictional work developed by the tire-road contact. In this study, an approach is proposed to estimate the tire-road friction during steady-state longitudinal and cornering maneuvers. Using this approach, a qualitative formula for tire wear evaluation is developed, and conceptual design analyses of cornering maneuvers are performed using simplified vehicle models. The influence of some design parameters such as cornering stiffness, the distance between the axles, and the steer angle ratio between the steering axles for vehicles with two steering axles is evaluated. The proposed methodology allows the designer to predict tire wear using simplified vehicle models during the conceptual design phase.     

A self-powering system based on tire deformation during driving

Tire intelligence is vital in the improvement of the safety of vehicles because the tire supports the car body and is the contact point between the vehicle and the road. To create an intelligent tire, sensors must be installed to measure the behavior of the tire. However, it is difficult to apply a wired sensor system on the wheel of the tire. Hence, it is necessary to implement a self-powering, wireless system (a type of energy harvesting system) that can be mounted inside the tire. The purpose of this study is to convert the strain energy caused by deformation of the tire while driving into useful electrical energy to supply the sensor system. A flexible piezofiber is utilized for the energy conversion. The variation in strain, due to changes in speed, load, and the internal pressure of the tire, was measured along two axial directions to evaluate the amount of available strain energy. The amount of strain changed from 0.15% to 0.8%. To predict the amount of available energy from a tire, we perform an analysis of the relationship between the strain and the voltage. In addition, experiments for impedance matching between piezofiber and related circuits were conducted to optimize the external loads for transferring energy efficiently. Based on the procedure mentioned above, at least 0.58 mJ of electrical energy can be generated by using the laterally oriented strain (1500 to 2500 micro strain). The result of this study is expected to enhance the potential realization of self-generating wireless sensor systems for so-called ??intelligent?? tires.     

Non-natural equilibrium contour design for radial tire and its influence on tire performance

Two types of radial tire 11.00R20 and 385/65R22.5 are chosen as the research objects, and their carcass contours are redesigned by using Sakai Hideo’s, Frank’s and the new non-natural equilibrium contour design theories, which were based on analyzing the current non-equilibrium contour design theories of radial tire. Then the tire wear, rolling resistance and grip performance of the two radial tires designed by different non-natural equilibrium contour design theories are comprehensively analyzed with the finite element software ABAQUS. The results show that Frank’s contour design theory can reduce tire wear; the new non-natural equilibrium contour design theory can enhance tire wear, rolling resistance performance, etc. It is also found that the tire carcass contour has great influence on tire performance, especially on the tire rolling resistance. The new non-natural equilibrium contour theory provides a guidance to reduce the tire rolling resistance, and it can break through the target conflicts in tire performance. The tire with the new non-natural equilibrium carcass contour can enhance its comprehensive performance.     

基于神经网络方法的台试轮胎滚动阻力模型研究

采用反拖测试方法,在双滚筒式底盘测功机上进行了大量有关轮胎滚动阻力影响因素(包括胎压、速度、载荷、胎温及轮胎的型号等)的交叉试验。以这些因素作为神经网络的训练输入参数,建立了台试轮胎滚动阻力神经网络模型。通过试验验证,用神经网络模型预估基于双滚筒测试的轮胎滚动阻力误差小于4%,为利用底盘测功机准确测试汽车动力性等工作奠定了基础。     

连续刚构桥施工控制中的参数识别方法研究

参数识别是大跨径桥梁施工控制分析中的重点.以某连续刚构桥为例,通过参数敏感度分析确定了连续刚构桥在施工过程中对桥梁线形影响较大的参数,并通过一系列方法得到学习样本,基于神经网络法对待识别参数进行识别修正,并进行下阶段的施工状态的预测,从而使施工过程中各个节段粱体的立模标高得到有效的控制.     

Development of a model for an air brake system with leaks and a scheme for the estimation of the steady-state pushrod stroke

Brake systems in trucks are crucial for ensuring the safety of vehicles and passengers on the roadways. Most trucks in the USA are equipped with S-cam drum brake systems and they are sensitive to maintenance. Brake deficiencies such as leaks and out-of-adjustment of the pushrod are a major cause of accidents involving trucks. Leaks in the air brake systems drastically affect braking performance by decreasing the maximum attainable braking pressure and also increasing the time required to attain the same, thereby resulting in longer stopping distances. Out-of-adjustment of the pushrod leads to loss of braking torque even if no leaks are present in the air brake system. In this paper, we present a mathematical model for an air brake system in the presence of leaks, with a view towards developing a diagnostic system for the air brake system based on the models. Additionally, we present a scheme that estimates the severity of leak in terms of the mass flow rate of air leaking from the air brake system to the atmosphere. This scheme can be implemented using a simple look-up table. We also present a steady-state pushrod stroke estimation scheme, based on brake chamber pressure measurements in the absence of any leaks in the air brake system.     

基于烟花算法的PHEV能量管理策略参数优化

为改善插电式混合动力汽车(PHEV)的燃油经济性,提出一种基于规则的能量管理策略.结合智能网联汽车技术,利用烟花算法(F WA)结合系统约束条件,对能量管理策略参数进行优化,以求使车辆在变化的路况下能耗最低.为减轻沉重运算负荷,设计了一种事件触发机制来控制优化操作的启停.当车辆油耗超过预设上限则开始优化,一旦油耗满足预...     

适用于汽车转弯制动仿真的轮胎力学模型

通过对轮胎试验结果的分析,用统计拟合方法建立了一种适用于转弯制动联合工况仿真的轮胎力学模型。所建模型与实际情况接近,计算简便,在用理论分析建模困难时,而采用试验数据进行统计建模不失为一种有效的途径。     

Neural-empirical tyre model based on recursive lazy learning under combined longitudinal and lateral slip conditions

The behaviour of the tyre plays an important role in the vehicle handling. An accurate tyre model that estimates these forces and moments it is highly essential for the studies of vehicle behaviour. For the last ten years neural networks have attracted a great deal of attention in vehicle dynamics and control. Neural networks have been effectively applied to model complex systems due to their good learning capability. In this paper a recursive lazy learning method based on neural networks is considered to model the tyre characteristics under combined braking and cornering. The proposed method is validated by comparison with experimental obtained responses. Results show the estimated model correlates very well with the data obtained experimentally. Moreover, the neural model proposed allows to include the asymetric tyre behaviour in the tyre model without difficulty.     

Development of a valve and optimization of a tube for self-inflating tire

Worldwide, the tire market requires safe and eco-friendly tires. In this study, a self-inflating tire (SIT) was studied and manufactured. Self-inflating tire refers to a technique for maintaining appropriate tire pressure. An internal regulator senses when tire inflation pressure has dropped below the set air pressure. The tire boosts air through the valve when rolling and compressed air enters into the tire. This procedure keeps the tire air pressure at an appropriate level and increases tire safety. In this study, a regulator was used as a negative-pressure system. A check valve was selected the minute flow check valve depending on the shape of the configured system. In addition, the material of the tube was developed with excellent physical properties and resistances (elastic rebound, working temperature, etc.) owing to its complete compression and restoration. A tube performance tester was developed and a computer aided engineering (CAE) model was modeled for comparison with the test results. Using the tester and model, it was possible to optimize the shape of the tube and regulator. Finally, the reliability of the study was verified through the prototype test. The developed equipment and systems can be used for the manufacture of high-performance and safe tires.     

Traffic flow forecasting based on a hybrid model

Real-time traffic flow forecasting is of great importance in the development of advanced traffic management systems and advanced traveler information systems. Traffic flow is evaluated using time series, and the Autoregressive Integrated Moving Average (ARIMA) model has been commonly used for determining the regression-type relationship between historical and future data. However, the performance of the ARIMA model is limited by the difficulty of capturing nonlinear patterns and the challenges of diagnosing permanent white noises. Hence, a hybrid method of ARIMA-EGARCH-M-GED was developed with the intent to address those limitations. It combines the linear ARIMA model with a nonlinear model of Exponent Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) to capture heteroscedasticity (the variance of random error varying across the data) of traffic flow series. EGARCH in Mean (EGARCH-M), which corrects the expression of conditional variance by connecting the conditional mean directly with the variance, was introduced to better restrain the influence of abnormal data. Moreover, the tail of the generalized error distribution (GED) is better than that of the normal distribution in characterizing the features of time series, especially heteroscedasticity of residual sequences. Data collected from an interstate highway (I-80 in California) with a sampling period of 5 minutes were used to evaluate the performance of the proposed model. The results from the hybrid model were compared with ARIMA, an artificial neural network, and a K-nearest neighbor model. The results showed that the hybrid model outperformed the other methods in terms of accuracy and reliability. Overall, the proposed model performed well in tracking the features of measured data and controlling the impact of abnormal data.     

Comprehensive lateral driver model for critical maneuvering conditions

A new comprehensive driver model is presented for critical maneuvering conditions with more accurate dynamic control performance. In order to achieve a safe maneuvering mode, a new path planning scheme to maintain stability of the vehicle was designed. A new steering strategy, considering the errors of vehicle position and yaw angle between the real track and the planned path, was established to obtain the steering angle. Therefore, the vehicle can be adjusted to accurately follow the desired path with the driver model, and the stability of the vehicle and the smoothness of the steering angle input were comprehensively considered. Simulation results were used to validate the control performance in comparison with the optimal preview driver model proposed by Macadam.