Modeling and Simulation of Various Hybrid-Electric Configurations of the High-Mobility Multipurpose Wheeled Vehicle (HMMWV)

Although hybrid-electric vehicles have been studied mainly with the aim of increasing fuel economy, little has been done in order to improve both fuel economy and performance. However, vehicular-dynamic-performance characteristics such as acceleration and climbing ability are of prime importance in military vehicles such as the high-mobility multipurpose wheeled vehicle (HMMWV). This paper concentrates on the models that describe hybridized HMMWV vehicles and the simulation results of those models. Parallel and series configurations have been modeled using the advanced-vehicle-simulator software developed by the National Renewable Energy Laboratory. Both a retrofit approach and a constant-power approach have been tested, and the results are compared to the conventional model results. In addition, the effects of using smaller engines than the existing ones in hybrid HMMWV drive trains have been studied, and the results are compared to the data collected from an actual implementation of such a vehicle. Moreover, the integrated-starter/alternator (ISA) configuration has been considered, and the results were encouraging     

Modeling of a Series Hybrid Electric High-Mobility Multipurpose Wheeled Vehicle

In an effort to reduce fuel costs and gas emissions, the U.S. Army is looking into replacing their diesel high-mobility multipurpose wheeled vehicle (HMMWV) with hybrid electric vehicles. The aim of this paper is to present the simulation of the series hybrid electric HMMWV based on a multidomain model using Ansoft Simplorer. Emphasis is placed on the vehicle's transient response to desired speeds dictated by drive cycles based on an urban dynamometer driving schedule and SAE J227a Schedule D. Also included in this paper were the vehicle's responses to hill climbing up to 60% grade     

The Illinois Roadway Simulator: a mechatronic testbed for vehicledynamics and control

The Illinois Roadway Simulator (IRS) is a novel, mechatronic, scaled testbed used to study vehicle dynamics and controls. An overview of this system is presented, and individual hardware issues are addressed. System modeling results on the vehicles and hardware are introduced, and comparisons of the resulting dynamics are made with full-sized vehicles. Comparisons are made between dynamic responses of full-scale and IRS-scale vehicles. The method of dynamic similitude is a key to gaining confidence in the scaled testbed as an accurate representation of actual vehicles to a first approximation. The IRS is then used in a vehicle control case study to demonstrate the potential benefits of scaled investigations. The idea of driver-assisted control is formulated as a yaw-rate model-following problem based on the representation of the driver as a known disturbance model. The controller is designed and implemented to show that the vehicle's dynamics can be changed to match a prescribed reference model     

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.     

Optimal robust control of a contactless brake system using an eddy current

As vehicle speed increases, a more powerful brake system is required to ensure vehicle safety and its reliability. A contactless eddy current brake (ECB) is developed to take the superior advantages of fast anti-lock braking to the conventional hydraulic brake systems. Braking torque analysis is performed by using an approximate theoretical model and the model is modified through experiments to have a more reliable result. Designs of an ECB for a scaled model for demonstration and actual vehicle model are performed. Optimal torque control which minimizes a braking distance is achieved by maintaining a desired slip ratio corresponding to the road condition. Optimal controller which is robust to the varying road friction coefficients is designed by using a sliding mode controller. Simulation and experimental results for a scaled model are presented to investigate the performance of a contactless ECB.     

Efficient Drive Cycle Simulation

Drive cycle simulations of longitudinal vehicle models are important aids for the design and analysis of power trains, and tools currently on the market mainly use two different methods for such simulations: the forward dynamic and quasi-static inverse simulations. Here, a known theory for the stable inversion of nonlinear systems is used to combine the fast simulation times of the quasi-static inverse simulation with the ability of the forward dynamic simulation to include transient dynamics. The stable inversion technique and a new implicit driver model together form a new concept: inverse dynamic simulation. This technique is demonstrated to be feasible for vehicle propulsion simulation and specifically for three power train applications that include important dynamics that cannot be handled using quasi-static inverse simulation. The extensions are engine dynamics, driveline dynamics, and gas flow dynamics for diesel engines, which are also selected to represent important properties, such as zero dynamics, resonances, and nonminimum-phase systems. It is shown that inverse dynamic simulation is easy to set up, gives short simulation times, and gives consistent results for design space exploration. This makes inverse dynamic simulation a suitable method to use for drive cycle simulation, particularly in situations requiring many simulations, such as optimization over design space, power train configuration optimization, or the development of power train control strategies.     

纯电动中型客车动力系统参数匹配及性能研究

针对现有车辆改装技术缺乏相应的参数匹配研究及动力学仿真分析,提出利用参数匹配和动力学分析研究汽车改制的方法,该方法以“LS6600C1”型普通中型客车改装的纯电动试验车为研究对象,对动力系统进行参数匹配设计,并利用电动汽车仿真软件ADVISOR建立相应的纯电动汽车动力系统及整车仿真模型,对整车模型的最高车速、加速能力、爬坡性能和续驶里程等指标进行了仿真研究。结果表明,典型工况下改装后的纯电动试验车续驶里程、最高车速、加速性能和爬坡性能等均满足普通中型客车的运行要求和使用条件,该改装技术具有广泛的应用前景。     

履带车辆行驶平顺性仿真及试验

基于虚拟样机技术,结合三维造型软件、有限元分析和多体动力学软件,对履带车辆行驶平顺性仿真技术进行了研究.建立履带车辆的刚柔混合虚拟样机模型及随机不平路面模型,生成平顺性仿真模型系统,通过在F等级随机路面行驶仿真,得到车辆行驶时驾驶员座椅位置振动加速度曲线,根据评价标准对车辆进行平顺性评价,并与实车试验测试数据的计算结果进行对比分析.结果表明,仿真模型系统及评价方法合理,可以为提高和改善履带车辆的机动性能提供有效的方法和手段.     

Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.     

缩比模型试验技术在射频仿真暗室设计中的应用

根据电磁系统的缩比模型试验技术理论,结合射频仿真暗室设计实践,提出利用缩比模型试验验证仿真计算结果,提高射频仿真暗室仿真辅助设计效果的方法,并且通过缩比试验与仿真结果的比对,证明了该方法在微波暗室设计中应用的可行性。     

Load sensing bearing based road-tyre friction estimation considering combined tyre slip

This work discusses a road-tyre friction estimator considering combined tyre slip. The friction estimator design is motivated by its importance in vehicle dynamics control as accurate friction estimation can improve performance and safety. The estimator uses tyre force measurements from Load Sensing Bearing (LSB) technology and does not rely on parameterized tyre model. The tyre force measurements benefit the estimator mainly because of the uncertainties and nonlinearities of the tyre force characteristics. The proposed estimator uses tyre slip and tyre force representations where the longitudinal and lateral tyre slips and forces are combined into a single tyre slip and tyre force values. This representation makes the method effective during pure longitudinal dynamics, pure lateral dynamics and for combined slip. In addition, individual tyre-road friction estimation is possible with the proposed estimator and a computationally inexpensive algorithm, suitable for real-time implementation, is used to estimate the friction. The estimator is studied in simulation during pure braking, pure cornering and for combined slip. Further, the estimator is simulated in closed loop with a yaw rate controller to study whether the estimator improves vehicle safety. Finally the estimator is validated using test data from several maneuvers performed on a test vehicle instrumented with LSB technology.     

Multi-objective control synthesis: an application to 4WS passenger vehicles

The vehicle dynamics and control play an important role in an automated highway system for passenger cars. This study addresses the problem of designing active controllers for four-wheel-steering (4WS) vehicles. We first obtain a set of linear maneuvering equations representing the four-wheel steering motions and independent wheel torques for lateral/directional plus roll dynamics. We then formulate simultaneous H₂ and H_∞ (sub)-optimal controls with a desired pole assignment via linear matrix inequalities (LMIs). The steering angles are actively controlled by steering wheel commands through the actuator mechanisms for the lateral/directional and roll motions. Further the wheel power and braking are directly controlled by independent torques. Numerical simulations are performed on a complex vehicle model in order to evaluate the vehicle performance (noise and disturbance attenuation), stability, and robustness under a given class of uncertainty. Finally, the presented autopilot controller provides greater maneuverability and improved directional stability for passenger vehicles.     

Sliding mode based powertrain control for efficiency improvement in series hybrid-electric vehicles

This study involves the improvement of overall efficiency in series hybrid-electric vehicles (SHEVs) by restricting the operation of the engine to the optimal efficiency region, using a control strategy based on two chattering-free sliding mode controllers (SMCs). One of the designed SMCs performs engine speed control, while the other controls the engine/generator torque, together achieving the engine operation in the optimal efficiency region of the torque-speed curve. The control strategy is designed for application on a SHEV converted from a standard high mobility multipurpose wheeled vehicle (HMMWV) and simulated by using the Matlab-based PNGV Systems Analysis Toolkit (PSAT). The performance of the control strategy is compared with that of the original PSAT model, which utilizes PI controllers, a feedforward term for the engine torque, and comprehensive maps for the engine, generator and power converter (static only), which constitute the auxiliary power unit (APU). In this study, in spite of the simple modeling approach taken to model the APU and the optimal efficiency region, an improved performance has been achieved with the new SMC based strategy in terms of overall efficiency, engine efficiency, fuel economy, and emissions. The control strategy developed in this work is the first known application of SMC to SHEVs, and offers a simple, effective and modular approach to problems related to SHEVs.     

Vehicle Full-State Estimation and Prediction System Using State Observers

This paper presents a novel vehicle full-state estimation and prediction system that employs a “full-state vehicle model” together with lateral acceleration, longitudinal velocity, and suspension displacement sensors to obtain the current and future vehicle state information. The full-state vehicle model is a vehicle model with 6 degrees of freedom (DOFs) and is described by 20-state nonlinear differential equations. The proposed approach differs from those in most of the existing literatures in three aspects. First, the road angles and the nonlinear suspension systems are incorporated into the vehicle modeling. Second, the “switching observer scheme” is introduced to significantly reduce the heavy work load that is required for the mathematical derivations. Finally, the full-state vehicle model is employed to predict the vehicle dynamics at future times. The simulation results show that the proposed system can accurately estimate and predict the state values. The relative accuracy of the state estimation is 2.66% on average and 2.86% on average of the state prediction. Furthermore, the proposed system can predict whether the vehicle rollover will occur when a vehicle performs a quick turn on a slope road.      

基于接触动力学的座圈动态响应仿真分析

座圈是履带车辆上的一个关键件,根据接触动力学理论,对座圈子系统的动态响应进行了分析研究。首先结合有限元和多体动力学分析技术,创建面向柔性下座圈的整车刚柔混合模型。考虑座圈子系统中座圈与滚珠的动态接触关系,采用边界盒法搜索上座圈—滚珠—下座圈之间的接触状态,由Hertz接触理论建立非线性弹簧阻尼模型计算接触力。然后以典型工况下座圈动态响应分析为例,对整车样机进行接触动力学仿真分析,获得了柔性下座圈的应力分布及变化情况。     

Development of an automated steering vehicle based on roadwaymagnets-a case study of mechatronic system design

Automated steering control is a crucial element of vehicle automation. The California PATH Program at the University of California at Berkeley has developed one such system using magnetic markers embedded under the roadway for lateral guidance. This system was demonstrated during the August 1997 National Automated Highway System Consortium Feasibility Demonstration, San Diego, CA, without a single failure. Developing a successful demonstration system not only required theoretical understanding of the various control problems involved, but also strong appreciation of all practical issues. In the paper, the comprehensive process of developing such automated steering control system is described. This process consists of control objectives' determination, system structure definition, vehicle dynamics validation, lateral sensing system development, steering actuator design, test track installation, control algorithm development, software/hardware integration, and vehicle testing. The entire process also serves as a good case study for mechatronic system design integrating mechanical components, electronic devices, intelligence, and feedback control to perform vehicle automation functions     

Robust energy-to-peak sideslip angle estimation with applications to ground vehicles

In this paper, the observer design problem for the sideslip angle of ground vehicles is investigated. The sideslip angle is an important signal for the vehicle lateral stability, which is not measurable by using an affordable physical sensor. Therefore, we aim to estimate the sideslip angle with the yaw rate measurements by employing the vehicle dynamics. The nonlinear lateral dynamics is modeled firstly. As the tyre model is nonlinear and the road adhesive coefficient is subject to a large variation, the nonlinear lateral dynamics is transformed into an uncertain model. Considering the variation of longitudinal velocity, an uncertain linear-parameter-varying (LPV) system is obtained. Based on the LPV model, a gain-scheduling observer is proposed and the observer gain can be determined with off-line computation and on-line computation. The off-line computation includes the calculation of a set of linear matrix inequalities and the on-line computation contains several algebraic operations. The proposed design methodology is applied to a four-wheel-independent-drive electric vehicle in simulation. It infers from different maneuvers that the designed observer has a good performance on estimating the sideslip angle.     

A lateral position sensing system for automated vehicle following

This paper investigates the use of photoresistive light sensor arrays as a possible lateral position sensing system for a vehicle, or several vehicles, following a lead vehicle under separate control. A brief motivation for the use of such a sensing array is followed by a derivation of an appropriate sensor layout. It is shown that the sensing array has several benefits, including cost, simplicity, redundancy, and near linearity. Experimental results are given for a scaled vehicle following manoeuvre using a simple lateral control strategy. The results show that the sensor array may be attractive for lateral alignment in vehicle-following manoeuvres     

Estimation of sideslip angle and cornering stiffness of an articulated vehicle using a constrained lateral dynamics model

In this paper, a constrained lateral dynamics model of articulated vehicles and an algorithm for estimating sideslip angle and cornering stiffness are proposed. The articulated vehicle was modeled using the bicycle model, linear tire model, and modified Dug-off model. The normal force of each axle included in the model was estimated based on the longitudinal load transfer model. Physical constraints were applied to reduce model states. Accurate sideslip angle and cornering stiffness are essential for vehicle control safety and autonomous driving performance. The sideslip angle and cornering stiffness were simultaneously estimated using a dual linear time-varying (LTV) Kalman filter. The observability matrix guaranteed the convergence of the proposed estimation algorithm. The estimation performance was verified by simulation with TruckSim and an experiment using an articulated bus.