Research on the Application of CarSim in Vehicle Simulation and Development

In the process of vehicle development,in order to reduce the actual vehicle test,get better economic benefits,speed up the development process,with simulation software,the development of vehicles or subsystems simulation has become an important part in the development process. As vehicle simulation software for parametric modeling,CarSim is a simple modeling process,rapid and accurate simulation,and can realize the simulation of open and close rings,and it is gradually popularized in vehicle research and development. This paper introduces the CarSim software,and then introduces the development of CarSim software in recent years.Based on the application of CarSim,this paper introduces it in all aspects of vehicle research and development,and finally summarizes it and puts forward some suggestions. Offering help for CarSim in vehicle research and development in the future,and building a certain foundation.

Multiple Purpose Simulation for Electric Vehicles

Aim Toshorten integral design period of electric vehicles Methods The electric vehicle simulation program(EVSP), a modular user-friendly program which is written in Borland C++ OWL for Windows was developed. Results EVSP allows simulating the dynamic and the economy performance of electric vehicles.EVSP provides many kinds of data input module,a large components library of electric vehicles and several kinds of speed cycle with these library,it is easily to develop a new concept of different drive trains or even to compare or improve the existing electric vehicles. The paper simulated the performance of YW6120DD Electric Bus, and analyzed the test results comparing with simulation results Conclusion The simulation results indicate that the EVSP may contribute to the developments of electric vehicles in general and the definition of the optimal match management in the drive train in particular.

PERFORMANCE SIMULATION OF VEHICLES EQUIPPED WITH TRACTION DRIVE CVTS

A computer model for the performance simulation of vehicles equipped with traction drive continuously variable transmission （CVT） is presented. The model integrates the traction drive CVT subsystem into an existing overall vehicle system. The characteristics of engine output torque are formulated using neural networks, and torque converter is modeled using lookup tables. Component inputs and outputs are coupled in the dynamic equations and interfaces in the powertrain system. The model simulation can provide evaluation of vehicle performance in drivability, fuel economy and emission levels for various drive ranges prior to the prototyping of the vehicle. As a design tool, the model assists engineers in understanding the effect ofpowertrain components on vehicle performance and making decisions in the selection of key design parameters. The model is implemented in the MATLAB/Simulink environment. The performance simulation of a test vehicle is included as a numerical example to illustrate the effectiveness of the model.

Dynamics Modeling and Simulation of Autonomous Underwater Vehicles with Appendages

To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle＇s （AUV） motion controller, a six-degree of freedom （6-DOF） dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV＇s motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages.

SEMI-ACTIVE CONTROL OF VEHICLE SUSPENSION WITH MAGNETO-RHEOLOGICAL DAMPERS:PART III—EXPERIMENTAL VALIDATION

A hardware-in-the-loop （HIL） test and simulation platform is developed in the laboratory, so as to validate the performance characteristics of the proposed skyhook-based asymmetric semi-active controller in Part I, and examine the validity of the proposed MR-damper model in a system surrounding. A real-time monitor is designed to assess and monitor the responses of the quarter-vehicle model in the HIL platform, and to select the excitation, controller synthesis, and the output displays. A drive current circuit hardware employing PID feedback technique is developed to compensate for the time delays from the servo-controller and drive current circuit, in which a small resistance is integrated in the current amplifier circuit to provide the feedback signal. The experiments were performed to measure the responses of the quarter-vehicle MR-suspension models with fixed current and the proposed semi-active MR-damping variations, under harmonic, rounded pulse and random road excitations. The measured data were compared with the corresponding model results to examine the model and controller validity, and revealed generally good agreements in the model and tested results and very little sensitivity of the tested responses to variations in the sprung mass. The HIL test results validate the effectiveness of the proposed skyhook-based semi-active asymmetric controller and its high robustness against the vehicle load variations in view of the intelligent vehicle suspension design.

A leveling mechanism for the platform based on booms-constraint control of aerial vehicle

In order to achieve an automatic leveling function for work platforms of aerial vehicles with mixed-booms( MAV) in full elevating domain,an auto-leveling mechanism for the platform is proposed based on a control method of booms-constraint,where mixed-boom structures and elevating characteristics are considered. Three models of constraint strategies include non-constraint model,elevating constraint model and lowering constraint model,which is designed to meet the leveling requirements in full working extent. Through the hydro-mechatronic unified modeling,a virtual prototype model is set up based on the auto-leveling mechanism,and leveling performances of the platform are studied during booms elevating to the maximum working height and extent. Simulation results show that the control method of booms-constraint can realize auto-leveling of the platform under two typical working conditions,meanwhile a leveling deviation appears at the constrained point,but the platform inclination is adjusted in the permissible range. The control method does not only restrict booms' freedom elevating to a certain extent,but also impacts the booms extending to the maximum working range. Experimental results verify that the auto-leveling mechanism based on booms-constraint control is valid and rational,which provides an effective technology approach for development of the platform leveling of MAV.

Neural Network-Based State of Charge Estimation Method for Lithium-ion Batteries Based on Temperature

Lithium-ion batteries are commonly used in electric vehicles,mobile phones,and laptops.These batteries demonstrate several advantages,such as environmental friendliness,high energy density,and long life.However,battery overcharging and overdischarging may occur if the batteries are not monitored continuously.Overcharging causesfire and explosion casualties,and overdischar-ging causes a reduction in the battery capacity and life.In addition,the internal resistance of such batteries varies depending on their external temperature,elec-trolyte,cathode material,and other factors;the capacity of the batteries decreases with temperature.In this study,we develop a method for estimating the state of charge(SOC)using a neural network model that is best suited to the external tem-perature of such batteries based on their characteristics.During our simulation,we acquired data at temperatures of 25°C,30°C,35°C,and 40°C.Based on the tem-perature parameters,the voltage,current,and time parameters were obtained,and six cycles of the parameters based on the temperature were used for the experi-ment.Experimental data to verify the proposed method were obtained through a discharge experiment conducted using a vehicle driving simulator.The experi-mental data were provided as inputs to three types of neural network models:mul-tilayer neural network(MNN),long short-term memory(LSTM),and gated recurrent unit(GRU).The neural network models were trained and optimized for the specific temperatures measured during the experiment,and the SOC was estimated by selecting the most suitable model for each temperature.The experimental results revealed that the mean absolute errors of the MNN,LSTM,and GRU using the proposed method were 2.17%,2.19%,and 2.15%,respec-tively,which are better than those of the conventional method(4.47%,4.60%,and 4.40%).Finally,SOC estimation based on GRU using the proposed method was found to be 2.15%,which was the most accurate.

Optimization Framework for Conceptual Powertrain Design

With an increasing number of vehicles with alternative powertrains, the choice of the most appropriate powertrain system for a vehicle class or a load cycle is challenging. This paper introduces a method to design an optimal alternative powertrain based on a longitudinal dynamic simulation. The objective function of the minimization problem describes the characteristic map of the traction system. The goal of the optimization is to minimize fuel consumption respectively energy demand. Different types of propulsion systems are investigated. The results show that the proposed method delivers useful alternative powertrains by applying an optimization with reasonable restrictions.

Numerical investigation on properties of attack angle for an opposing jet thermal protection system

The three-dimensional Navier Stokes equation and the k-ε viscous model are used to simulate the attack angle characteristics of a hemisphere nose-tip with an opposing jet thermal protection system in supersonic flow conditions. The numerical method is validated by the relevant experiment. The flow field parameters, aerodynamic forces, and surface heat flux distributions for attack angles of 0°, 2°, 5°, 7°, and 10° are obtained. The detailed numerical results show that the cruise attack angle has a great influence on the flow field parameters, aerodynamic force, and surface heat flux distribution of the supersonic vehicle nose-tip with an opposing jet thermal protection system. When the attack angle reaches 10°, the heat flux on the windward generatrix is close to the maximal heat flux on the wall surface of the nose-tip without thermal protection system, thus the thermal protection has failed.

Study on ultracapacitor-battery hybrid power system for PHEV applications

For the battery only power system is hard to meet the energy and power requirements reasonably, a hybrid power system with uhracapacitor and battery is studied. A Topology structure is analyzed that the uhracapacitor system is connected with battery pack parallel after a bidirectional DC/DC converter. The ultracapacitor, battery and the hybrid power system are modeled. For the plug-in hybrid electric vehicle （PHEV） application, the control target and control strategy of the hybrid power system are put forward. From the simulation results based on the Chinese urban driving cycle, the hybrid power system could meet the peak power requirements reasonably while the battery pack＇ s current is controlled in a reasonable limit which will be helpful to optimize the battery pack＇ s working conditions to get long cycling life and high efficiency.

A Potential Flow Based Flight Simulator for an Underwater Glider

Underwater gliders are recent innovative types of autonomous underwater vehicles （AUVs） used in ocean exploration and observation. They adjust their buoyancy to dive and to return to the ocean surface. During the change of altitude, they use the hydrodynamic forces developed by their wings to move forward. Their flights are controlled by changing the position of their centers of gravity and their buoyancy to adjust their trim and heel angles. For better flight control, the understanding of the hydrodynamic behavior and the flight mechanics of the underwater glider is necessary. A 6-DOF motion simulator is coupled with an unsteady potential flow model for this purpose. In some specific cases, the numerical study demonstrates that an inappropriate stabilizer dimension can cause counter-steering behavior. The simulator can be used to improve the automatic flight control. It can also be used for the hydrodynamic design optimization of the devices.

Impact of combined alignments and adverse weather conditions on vehicle skidding

Roadways in Wyoming are characterized by challenging horizontal profiles,vertical profiles,a combination of the two and adverse weather conditions,all of which affect vehicle stability.In this study,we investigated the impact of different operating speeds when negotiating combined horizontal and vertical curves under unfavorable environmental conditions on Wyoming’s interstates via vehicle dynamics simulation software.The simulation tools provided the acting forces on each tire of the vehicle and the side friction(skidding)margins.This allowed for examining the interaction between vehicle dynamics and road geometry in such alignments.Also,linear regression analysis was implemented to investigate the skidding margins based on the simulation results to demonstrate when a vehicle is more likely to deviate from its desired trajectory.Specifically,this examines the contributing factors that significantly influence the skidding margins.The results indicated that:1)the skidding margins are dramatically decreased by adverse weather conditions even with lower degree of curvature and gradient values of combined curves and more particularly at higher operating speeds conditions.Increasing the vehicle speed on the curve by 10%,the skidding margin dropped by 15%.2)Compared to heavy trucks and sports utility vehicles(SUVs),passenger cars require the highest side friction demand.3)The effect of applying brakes on vehicle stability depends on the road surface condition;applying the brakes on snowy road surfaces increases the potential of vehicle skidding especially for heavy trucks.This study assessed the curve speed limits and showed how important to assign safe and appropriate limits speed since the skidding likelihood is significantly sensitive to the vehicle speeds.This study is beneficial to Wyoming’s roadway agencies since hazardous sections having combined horizontal and vertical curves are identified.Also,critical situations that require additional attention from law enforcement agencies are pinpointed.Finally,recommendations that are valuable to roadway agencies are made based on this study’s findings.

Prediction of Spatiotemporal Evolution of Urban Traffic Emissions Based on Taxi Trajectories

With the rapid increase of the amount of vehicles in urban areas,the pollution of vehicle emissions is becoming more and more serious.Precise prediction of the spatiotemporal evolution of urban traffic emissions plays a great role in urban planning and policy making.Most existing methods usually focus on estimating vehicle emissions at historical or current moments which cannot well meet the demands of future planning.Recent work has started to pay attention to the evolution of vehicle emissions at future moments using multiple attributes related to emissions,however,they are not effective and efficient enough in the combination and utilization of different inputs.To address this issue,we propose a joint framework to predict the future evolution of vehicle emissions based on the GPS trajectories of taxis with a multi-channel spatiotemporal network and the motor vehicle emission simulator(MOVES)model.Specifically,we first estimate the spatial distribution matrices with GPS trajectories through map-matching algorithms.These matrices can reflect the attributes related to the traffic status of road networks such as volume,speed and acceleration.Then,our multi-channel spatiotemporal network is used to efficiently combine three key attributes(volume,speed and acceleration)through the feature sharing mechanism and generate a precise prediction of them in the future period.Finally,we adopt an MOVES model to estimate vehicle emissions by integrating several traffic factors including the predicted traffic states,road networks and the statistical information of urban vehicles.We evaluate our model on the Xi′an taxi GPS trajectories dataset.Experiments show that our proposed network can effectively predict the temporal evolution of vehicle emissions.