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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

Plug-in Hybrid Electric Vehicles (PHEVs) have demonstrated the potential to provide significant reduction in fuel use across a wide range of dynamometer test driving cycles. Companies and research organizations are involved in numerous research activities related to PHEVs. One of the current unknowns is the impact of driving behavior and standard test procedure on the true benefits of PHEVs from a worldwide perspective. To address this issue, five different PHEV powertrain configurations (input split, parallel, series, series-output split and series-parallel), implemented on vehicles with different all-electric ranges (AERs), were analyzed on three different standard cycles (i.e., Urban Dynamometer Driving Schedule, Highway Fuel Economy Test, and New European Driving Cycle). Component sizes, manufacturing cost, and fuel consumption were analyzed for a midsize car in model year 2020 through the use of vehicle system simulations.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

Because Plug-in Hybrid Electric Vehicles (PHEVs) substitute electrical power from the utility grid for fuel, they have the potential to reduce petroleum use significantly. However, adoption of PHEVs has been hindered by expensive, low-energy batteries. Recent improvements in Li-ion batteries and hybrid control have addressed battery-related issues and have brought PHEVs within reach. The FreedomCAR Office of Vehicle Technology has a program that studies the potential benefit of PHEVs. This program also attempts to clarify and refine the requirements for PHEV components. Because the battery appears to be the main technical barrier, both from a performance and cost perspective, the main efforts have been focused on that component. Working with FreedomCAR energy storage and vehicle experts, Argonne National Laboratory (Argonne) researchers have developed a process to define the requirements of energy storage systems for plug-in applications.

Hybrid Electric Vehicle (HEV) owners have reported significantly lower fuel economy than the published estimates. Under on-road driving conditions, vehicle acceleration, speed, and stop time differ from those on the normalized test procedures. To explain the sensitivity, several vehicles, both conventional and hybrid electric, were tested at Argonne National Laboratory. The tests demonstrated that the fuel economy of Prius MY04 was more sensitive to drive-cycle variations. However, because of the difficulty in instrumenting every component, an in-depth analysis and quantification of the reasons behind the higher sensitivity was not possible. In this paper, we will use validated models of the tested vehicles and reproduce the trends observed during testing. Using PSAT, the FreedomCAR vehicle simulation tool, we will quantify the impact of the main component parameters, including component efficiency and regenerative braking.

Developed by the U.S. Environmental Protection Agency (EPA), the Multi-scale mOtor Vehicle Emission Simulator (MOVES) is used to estimate inventories and projections through 2050 at the county or national level for energy consumption, nitrous oxide (N2O), and methane (CH4) from highway vehicles. To simulate a large number of vehicles and fleets on numerous driving cycles, EPA developed a binning technique characterizing the energy rate for varying Vehicle Specific Power (VSP) under predefined vehicle speed ranges. The methodology is based upon the assumption that the vehicle behaves the same way for a predefined vehicle speed and power demand. While this has been validated for conventional vehicles, it has not been for advanced vehicle powertrains, including hybrid electric vehicles (HEVs) where the engine can be ON or OFF depending upon the battery State-of-Charge (SOC).

Argonne National Laboratory (Argonne) and Idaho National Laboratory (INL), working with the FreedomCAR and Fuels Partnership, lead activities in vehicle dynamometer and fleet testing as well as in modeling activities. By using Argonne’s Advanced Powertrain Research Facility (APRF), the General Motors (GM) Tahoe 2-mode was instrumented and tested in the 4-wheel-drive test facility. Measurements included both sensors and controller area network (CAN) messages. In this paper, we describe the vehicle instrumentation as well as the test results. On the basis of the analysis performed, we discuss the vehicle model developed in Argonne’s vehicle simulation tool, the Powertrain System Analysis Toolkit (PSAT), and its comparison with test data. Finally, on-road vehicle data, performed by INL, is discussed and compared with the dynamometer results.

Michigan Technological University has established a broad-based university-wide research initiative, termed Wood-to-Wheels (W2W), to develop and evaluate improved technologies for growing, harvesting, converting, and using woody biomass in renewable transportation fuel applications. The W2W program bridges the entire biomass development-production-consumption life cycle with research in areas including forest resources, bioprocessing, engine/vehicle systems, and sustainable decisions. The W2W chain establishes a closed cycle of carbon between the atmosphere, woody biomass, fuels, and vehicular systems that can reduce the accumulation of CO2 in the atmosphere. This paper will summarize the activities associated with the Wood-to-Wheels initiative and describe challenges and the potential benefits that are achievable.

Rising fuel costs, increased regulations, and heightened customer sensitivity to energy efficiency has prompted the evaluation of numerous powertrain technology improvements to introduce into production. The actual impact of such technologies can differ broadly, depending on the technology or application. To evaluate the fuel consumption impact, various baseline vehicles have been created and simulated by using Argonne National Laboratory's vehicle modeling and simulation tool, the Powertrain Systems Analysis Toolkit (PSAT). This paper provides a quantitative evaluation of several technologies or combinations of technologies. First, we assess the impact of single technologies, including vehicle/chassis characteristics, such as weight, aerodynamics, or rolling resistance. Next, we consider advanced powertrain technologies, ranging from dieselization to transmissions with a higher gear number, and hybridization.

This paper analyzes fuel economy benefits of direct hydrogen and gasoline reformer fuel cell vehicles, with special focus on cold-start impacts on these fuel cell based vehicles. Comparing several existing influential studies reveals that the most probable estimates from these studies differ greatly on the implied benefits of both types of fuel cell vehicles at the tank-to-wheel level (vehicle-powertrain efficiency and/or specific power), leading to great uncertainties in estimating well-to-wheel fuel energy and/or greenhouse gas (GHG) emission reduction potentials. This paper first addresses methodological issues to influence the outcome of these analyses. With one exception, we find that these studies consistently ignore cold-start and warm-up issues, which play important roles in determining both energy penalties and start-up time of fuel cell vehicles. To better understand cold-start and warm-up behavior, this paper examines approaches and results based on two available U.S.

This study involves the battery requirements for a fuel cell-powered hybrid electric vehicle. The performances of the vehicle [a 3200-lb (1455-kg) sedan], the fuel cell, and the battery were evaluated in a vehicle simulation. Most of the attention was given to the design and performance of the battery, a lithium-ion, manganese spinel-graphite system of 75-kW power to be used with a 50-kW fuel cell. The total power performance of the system was excellent at the full operating temperatures of the fuel cell and battery. The battery cycling duty is very moderate, as regenerative braking for the Federal Urban Driving Schedule and the Highway Fuel Economy Test cycles can do all charging of the battery. Cold start-up at 20°C is straightforward, with full power available immediately.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. When considering the introduction of advanced vehicles, a complete well-to-wheel evaluation must be performed to determine the potential impact of a technology on carbon dioxide and Green House Gases (GHGs) emissions. Several modeling tools developed by Argonne National Laboratory (ANL) were used to evaluate the impact of advanced powertrain configurations. The Powertrain System Analysis Toolkit (PSAT) transient vehicle simulation software was used with a variety of fuel cell system models derived from the General Computational Toolkit (GCtool) for pump-to-wheel (PTW) analysis, and GREET (Green house gases, Regulated Emissions and Energy use in Transportation) was used for well-to-pump (WTP) analysis. This paper compares advanced propulsion technologies on a well-to-wheel energy basis by using current technology for conventional, hybrid and fuel cell technologies.

Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. As the entire powertrain system needs to be optimized, the requirements of each component to achieve FreedomCAR goals need to be determined. With the collaboration of FreedomCAR fuel cell, energy storage, and vehicle Technical Teams, Argonne National Laboratory (ANL) used several modeling tools to define the energy storage requirements for fuel cell vehicles. For example, the Powertrain System Analysis Toolkit (PSAT), which is a transient vehicle simulation software, was used with a transient fuel cell model derived from the General Computational Toolkit (GCtool). This paper describes the impact of degree of hybridization, control strategy, and energy storage technology on energy storage requirements for a fuel cell SUV vehicle platform.

This paper describes the integration of a Modal Energy and Emissions Model (MEEM) into a hybrid-electric vehicle simulation model, the PNGV System Analytic Toolkits (PSAT). PSAT is a forward-looking computer simulation model for advanced-technology vehicles. MEEM is a vehicle fuel-consumption and emissions model developed by one of the authors for internal-combustion-engine (ICE) -powered vehicles. MEEM engine simulation module uses a power-demand physical model based on a parameterized analytical representation of engine fuel and emissions production. One major advantage of MEEM is that it does not rely on steady-state engine maps, which are usually not available for most production vehicles; rather, it depends on a list of engine parameters that are calibrated based on regular vehicle dynamometer testing. The integrated PSAT-MEEM model can be used effectively to predict fuel consumption and emissions of various ICE-powered vehicles with both conventional and hybrid power trains.

Living in the era of rising environmental sensibility and increasing gasoline prices, the development of a new environmentally friendly generation of vehicles becomes a necessity. Hybrid electric vehicles are one means of increasing propulsion system efficiency and decreasing pollutant emissions. In this paper, the series-parallel power-split configuration for Michigan Technological University's FutureTruck is analyzed. Mathematical equations that describe the hybrid power-split transmission are derived. The vehicle's differential equations of motion are developed and the system's need for a controller is shown. The engine's brake power and brake specific fuel consumption, as a function of its speed and throttle position, are experimentally determined. A control strategy is proposed to achieve fuel efficient engine operation. The developed control strategy has been implemented in a vehicle simulation and in the test vehicle.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software: the PNGV System Analysis Toolkit (PSAT). The importance of component models and the complexity involved in setting up optimized control strategies require validation of the models and controls developed in PSAT. Using ANL's Advanced Powertrain Test Facilities (APTF), more than 50 tests on the Honda Insight were used to validate the PSAT drivetrain configuration. Extensive instrumentation, including the half-shaft torque sensor, provides the data needed for through comparison of model results and test data. In this paper, we will first describe the process and the type of test used to validate the models. Then we will explain the tuning of the simulated vehicle control strategy, based on the analysis of the differences between test and simulation.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT, originally proprietary, has been used by both DOE and the “Big Three” as a modeling tool. The number of PSAT users has increased recently because 15 universities participating in the 2001 FutureTruck competition were given the software for their use. PSAT allows companies to look at new types of vehicles (hybrids) and choose the best configuration according to customer expectations within a minimum of time. PSAT, a forward-looking model, allows the user to simulate a large number of different configurations (conventional, series, parallel, and power split). PSAT is well suited for development of control strategies; by using accurate dynamics component models as its code, PSAT can be implemented directly and tested at the bench scale or in a vehicle.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.