Advanced Vehicle Simulator Research Articles

Designing efficient hybrid electric vehicles

Hybrid electric vehicles (HEVs) are increasingly gaining popularity due to their lower fuel consumption. Current hybrid vehicles mostly use their battery or the energy storage system (ESS) as a secondary source of power. If the ESS were to be used as a primary source of power, then the ESS size would be one of the important features in the design of an HEV. In addition, HEVs have to employ an intelligent energy management strategy to provide the best fuel economy in all driving situations. This article presents an investigation on the effect of the variation of the ESS size on the fuel economy of an HEV and the important design criteria involved in the design of the ESS. Simulations carried out using advanced vehicle simulator (ADVISOR) software show that fuel economy is not linearly related to ESS size and therefore the ESS needs to be designed based on the average daily driving distance and the driver behavior.

Application of the “Contact Convoy” Concept to Hybrid Electric Vehicles

This paper applies an intelligent intervehicle device (termed a ldquobridging damperrdquo) to a convoy of in-contact vehicles. The field of application is backup for future automated highways and operation of novel guided systems using vehicle-following control. The vehicle represented in computer simulations is a parallel hybrid electric automobile. Using the advanced vehicle simulator (ADVISOR) model, the vehicle representation is tuned to achieve matching of the overall force and power characteristics and the same performance over an urban driving cycle. The model for which a dedicated Matlab Toolbox was constructed is described. Simulation results compare the vehicle-following control on its own with a passive damper and a ldquoquasi-activerdquo damper that is controlled in collaboration with the vehicle's drivetrain. Using transient disturbances in the form of wind gusts and short gradients, power peaks and longitudinal ride quality (vibration dose value) are used to evaluate the performance.

Determination of Parameters of Motor Simulation Module Employed in ADVISOR

This paper deals with the determination of parameters in the motor module of advanced vehicle simulator (ADVISOR) which is an advanced vehicle simulation software. In the ADVISOR, the traction motor of vehicle is defined by efficiency map, maximum torque/speed curve and so forth. Due to the prevalence of interior permanent magnet synchronous motor (IPMSM), this paper mainly focuses on the calculation of efficiency map of IPMSM considering magnetic nonlinearity. Firstly, by means of numerical methods, the inductance and iron loss resistance are calculated. Next according to equivalent circuits, the motor characteristics including speed, torque and efficiency are investigated. Finally, the calculated efficiency result is verified by the experiment data, and all parameters are loaded and implemented in ADVISOR for testing.

Comprehensive Efficiency Modeling of Electric Traction Motor Drives for Hybrid Electric Vehicle Propulsion Applications

Extensive research done in the recent past has proven that power electronic converters and electric propulsion motors are extremely critical components for modern hybrid electric vehicle (HEV) propulsion applications. Therefore, it is essential that both the traction motor and the associated drive operate at their optimal efficiencies throughout the driving schedule. In typical HEV propulsion applications, the traction motor and the drive are used over the entire torque/speed operational range. In view of this fact, this paper aims at modeling the inverter and motor losses/efficiencies over typical city and highway driving schedules. The noteworthy losses within a typical three-phase dc/ac traction inverter, such as the switching and conduction losses for both the insulated-gate bipolar transistors and the antiparallel diodes, are modeled and simulated over the city and highway driving patterns. An induction motor (IM) is used for a medium-sized sport utility vehicle, which was modeled in the advanced vehicle simulator (ADVISOR) software. The significant IM losses that were considered in the study include the stator copper losses, rotor copper losses, and core losses. Thus, the average efficiencies of both the inverter drive and the induction traction motor are evaluated and summarized under city as well as highway driving conditions. Finally, based on the individual-model-based efficiency analysis, the overall traction motor drive system efficiency is estimated.

Modeling and Simulation of Electric and Hybrid Vehicles

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper discusses the need for modeling and simulation of electric and hybrid vehicles. Different modeling methods such as physics-based Resistive Companion Form technique and Bond Graph method are presented with powertrain component and system modeling examples. The modeling and simulation capabilities of existing tools such as Powertrain System Analysis Toolkit (PSAT), ADvanced VehIcle SimulatOR (ADVISOR), PSIM, and Virtual Test Bed are demonstrated through application examples. Since power electronics is indispensable in hybrid vehicles, the issue of numerical oscillations in dynamic simulations involving power electronics is briefly addressed. </para>

Dynamic modeling and simulation of an induction motor with adaptive backstepping design of an input-output feedback linearization controller in series hybrid electric vehicle

In this paper using adaptive backstepping approach an adaptive rotor flux observer which provides stator and rotor resistances estimation simultaneously for induction motor used in series hybrid electric vehicle is proposed. The controller of induction motor (IM) is designed based on input-output feedback linearization technique. Combining this controller with adaptive backstepping observer the system is robust against rotor and stator resistances uncertainties. In additional, mechanical components of a hybrid electric vehicle are called from the Advanced Vehicle Simulator Software Library and then linked with the electric motor. Finally, a typical series hybrid electric vehicle is modeled and investigated. Various tests, such as acceleration traversing ramp, and fuel consumption and emission are performed on the proposed model of a series hybrid vehicle. Computer simulation results obtained, confirm the validity and performance of the proposed IM control approach using for series hybrid electric vehicle.

Comprehensive drive train efficiency analysis of hybrid electric and fuel cell vehicles based on motor-controller efficiency modeling

From the point of view of overall hybrid electric vehicle (HEV) and fuel cell vehicle (FCV) drive train efficiency, the research focus is mainly on the efficiency analysis of the power train components, which prove to be an integral part of modern HEV and FCV drive trains. The critical portion of any HEV electrical system consists of a power electronic converter (inverter) and a suitable traction motor. Thus, the efficiency analysis of the inverter/motor is of prime importance for the calculation of the overall efficiency of the drive trains. This paper aims at modeling the efficiencies of the traction motor/controller through efficiency maps. Efficiency maps are a convenient way to represent motor drive systems of large and complex systems, like that of a HEV. The paper uses the advanced vehicle simulator (ADVISOR) software for the simulations of a large-sized car, similar to a Chevy Lumina, over the urban dynamometer-driving schedule and highway fuel economy test drive cycles. Furthermore, the paper investigates the traction motor efficiency maps and consequent overall drive train efficiencies of commercially available Honda Insight and Toyota Prius HEVs. In all the case studies, the aim is to analyze the overall drive train efficiency over the city and highway drive cycles based on the inverter/motor efficiency maps.

Evaluating PEM fuel cell system models

Abstract Many proton exchange membrane (PEM) fuel cell models have been reported in publications and some are available commercially. This paper helps users match their modeling needs with specific fuel cell models. The paper has three parts. First, it describes the model selection criteria for choosing a fuel cell model. Second, it applies these criteria to select state-of-the-art fuel cell models available in the literature and commercially. The advantages and disadvantages of commercial models are discussed. Third, the paper illustrates the process of choosing a fuel cell model with an example: the National Renewable Energy Laboratory’s (NREL’s) evaluation of two detailed stand-alone fuel cell system models. One is from Virginia Tech University, and the other is from Sweden’s Royal Institute of Technology. Both models have been integrated into NREL’s vehicle simulation model ADVISOR™ 2003 (Advanced Vehicle Simulator).

ADVISOR: a systems analysis tool for advanced vehicle modeling

This paper provides an overview of Advanced Vehicle Simulator (ADVISOR)—the US Department of Energy’s (DOE’s) ADVISOR written in the MATLAB/Simulink environment and developed by the National Renewable Energy Laboratory. ADVISOR provides the vehicle engineering community with an easy-to-use, flexible, yet robust and supported analysis package for advanced vehicle modeling. It is primarily used to quantify the fuel economy, the performance, and the emissions of vehicles that use alternative technologies including fuel cells, batteries, electric motors, and internal combustion engines in hybrid (i.e. multiple power sources) configurations. It excels at quantifying the relative change that can be expected due to the implementation of technology compared to a baseline scenario. ADVISOR’s capabilities and limitations are presented and the power source models that are included in ADVISOR are discussed. Finally, several applications of the tool are presented to highlight ADVISOR’s functionality. The content of this paper is based on a presentation made at the ‘Development of Advanced Battery Engineering Models’ workshop held in Crystal City, Virginia in August 2001.

Battery thermal models for hybrid vehicle simulations

This paper summarizes battery thermal modeling capabilities for: (1) an advanced vehicle simulator (ADVISOR); and (2) battery module and pack thermal design. The National Renewable Energy Laboratory’s (NREL’s) ADVISOR is developed in the Matlab/Simulink environment. There are several battery models in ADVISOR for various chemistry types. Each one of these models requires a thermal model to predict the temperature change that could affect battery performance parameters, such as resistance, capacity and state of charges. A lumped capacitance battery thermal model in the Matlab/Simulink environment was developed that included the ADVISOR battery performance models. For thermal evaluation and design of battery modules and packs, NREL has been using various computer aided engineering tools including commercial finite element analysis software. This paper will discuss the thermal ADVISOR battery model and its results, along with the results of finite element modeling that were presented at the workshop on “Development of Advanced Battery Engineering Models” in August 2001.

Battery performance models in ADVISOR

This paper summarizes battery modeling capabilities in ADVISOR—the National Renewable Energy Laboratory’s advanced vehicle simulator written in the Matlab/Simulink environment. ADVISOR’s Matlab-oriented battery models consist of the following: (1) an internal resistance model, (2) a resistance–capacitance ( RC) model, (3) a PNGV capacitance model, (4) a neural network (nnet) lead acid model, and (5) a fundamental lead acid battery model. For the models, the electric schematics (where applicable), thermal models, accuracy, existing datasets, and sample validation plots are presented. A brief summary of ADVISOR’s capabilities for co-simulation with Saber is presented, which links ADVISOR with Saber’s lead acid battery model. The models outlined in this paper were presented at the workshop on ‘Development of Advanced Battery Engineering Models’ in August 2001.

ADVISOR 2.1: a user-friendly advanced powertrain simulation using a combined backward/forward approach

ADVISOR 2.1 is the latest version of the National Renewable Energy Laboratory's advanced vehicle simulator. It was first developed in 1994 to support the US Department of Energy hybrid propulsion system program and is designed to be accurate, fast, flexible, easily sharable, and easy to use. This paper presents the model, focusing on its combination of forward- and backward-facing simulation approaches, and evaluates the model in terms of its design goals. ADVISOR predicts acceleration time to within 0.7% and energy use on the demanding US06 to within 0.6% for an underpowered series hybrid vehicle (0-100 km/h in 20 s). ADVISOR simulates vehicle performance on standard driving cycles between 2.6 and 8.0 times faster than a representative forward-facing vehicle model. Due in large part to ADVISOR's powerful graphical user interface and Web presence, over 800 users have downloaded ADVISOR from 45 different countries. Many of these users have contributed their own component data to the ADVISOR library.