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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.

In this paper, we consider smart charging and vehicle-to-home (V2H) technologies for plugin electric vehicles coordinated with home energy management systems (HEMS) for automated demand response. In this system, plugin electric vehicles automatically react to demand response events with or without HEMS’s coordination, while vehicles are charged and discharged (i.e., V2H) in appropriate time slots by taking into account demand response events, time-ofuse rate information, and users’ vehicle usage plan. We introduce three approaches on home energy management: centralized energy control, distributed energy control, and coordinated energy control. We implemented smart charging and V2H systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0, and SAE standards and the other using OpenADR 2.0b, ECHONET Lite, and ISO/IEC 15118.

This paper presents a modeling method for prediction of low-frequency road noise in a steady-state condition where rotating tires are excited by actual road profile undulation input. The proposed finite element (FE) tire model contains not only additional geometric stiffness related to inflation pressure and axle load but also Coriolis force and centrifugal force effects caused by tire rotation for precise road noise simulation. Road inputs act on the nodes of each rib in the contact patch of the stationary tire model and move along them at the driving velocity. The nodes are enforced to displace in frequency domain based on the measured road profile. Tire model accuracy was confirmed by the spindle forces on the rotating chassis drum up to 100Hz where Coriolis force effect should be considered. Full vehicle simulation results showed good agreement with the vibration measurement of front/rear suspension at two driving velocities.

This paper proposes a novel method of verifying comprehensive driver model used for the evaluation of driving safety systems, which is achieved by coupling the traffic simulation and the driving simulator (DS). The method consists of three-step procedure. In the first step, an actual driver operates a DS vehicle in the traffic flow controlled by the traffic simulation. Then in the next step, the actual driver is replaced by a driver model and the surrounding vehicle maneuvers are replayed using the recorded data from the first step. Then, the maneuver by the driver model is compared directly with the actual driver's maneuver along the simulation time steps.

The application of Model-Based Development (MBD) techniques for automotive control system and software development have become standard processes due to the potential for reduced development time and improved specification quality. In order to improve development productivity even further, it is imperative to introduce a systematic Verification and Validation (V&V) process to further minimize development time and human resources while ensuring control specification quality when developing large complex systems. Traditional methods for validating control specifications have been limited by control specification scale, structure and complexity as well as computational limitations restricting their application within a systematic model-based V&V process. In order to address these issues, Toyota developed Hierarchical Accumulative Validation (HAV) for systematically validating functionally structured executable control specifications.

A number of active safety systems are already developed to support drivers’ decision and action to help avoid accidents, but further enhancement of those active safety systems cannot be accomplished without increasing our understanding on driver behaviors and their interaction with vehicle systems. For this reason, a state-of-art driving simulator (DS) has been developed that creates very realistic scenarios as a means of realizing these requirements. The DS consists of a simulator cabin, turntable (inside the dome), a 6-DOF hexapod system, shakers (vehicle vertical vibration actuators), and a motion system capable of moving 35 meters longitudinally and 20 meters laterally. The system is also capable of projecting images of actual city streets and highways onto a 360° spherical screen inside of the dome. As a result, the DS is able to reproduce a driving environment that is very similar to real driving.

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.

With the support of Horiba and Horiba STEC, Toyota Motor Corporation has developed an exhaust emissions simulator to verify the accuracy of extremely low emissions measurement systems. It can reliably verify the accuracy (correlation) of each SULEV emission measurement system to within 5% under actual conditions. The simulator's method of simulating SULEV gasoline engine cold-start emissions is to inject bottled gases with known concentrations of each emission constituent to the base gas, which is clean exhaust gas from a SULEV vehicle with new fully warmed catalysts. First, the frequencies and dynamic ranges of the SULEV cold-start emissions were analyzed and the method of 2 injecting the bottled gases was considered based on the results of that analysis. A high level of repeatability and accuracy was attained for all injection flow ranges in the SULEV cold-start emission simulation by switching between high-response digital Mass Flow Controllers (MFCs) of different full scales.

We have developed a novel engine cycle simulation program (UniDES: universal diesel engine simulator) to reproduce the diesel combustion process over a wide range of engine operating parameters, such as the amount of injected fuel, the injection timing, and the EGR ratio. The approach described in this paper employs a zoning model, where the in-cylinder region is divided into up to five zones. We also applied a probability density function (PDF) concept to each zone to consider the effect of spatial non-homogeneities, such as local equivalence ratios and temperature, on the combustion characteristics. We linked this program to the commonly used commercial GT-Power® software (UniDES+GT). As a result, we were able to reproduce transient engine behavior very accurately.

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.

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.

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.

We developed a progressive system, “virtual and real simulator (V&R-S)” for engine. To innovate the process of engine development, the test system creates dynamic load of drivetrain, wheel, body and road with the virtual vehicle model. We set the phenomena such as drivetrain vibration for reproducing object of this system. The load is transmitted to the engine crankshaft end as torque with the connecting shaft made of fiberglass. The mainly developed technologies are the dynamometer with rotational inertia as low as engine, correction method of transmitted torque error of connecting shaft by H-infinity control. Thanks to these, we achieved the capability of optimization for most of dynamic characteristics (emission, fuel consumption, drivability) on engine test bench. And we now be able to limit real vehicle test to the final tuning. As a result, we have realized new engine evaluation and optimization process.

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.

This paper presents results on how the Equivalent Consumption Minimization Strategy (ECMS) penalty factor effects Lithium ion battery aging. The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’. Vehicle simulation using multiple combinations of highway and city drive cycles. For each combination of drive cycles, six ECMS penalty factor values are used. Battery aging is evaluated using a semi-empirical model combined with accumulated Ah-throughput method which uses, as an input, the battery state of charge trajectory from the vehicle simulations. The tradeoff between fuel cost and battery aging cost is explicitly displayed. In addition, the results provide insight into how driving behavior affects battery aging. The paper concludes with a discussion of the optimal balance between fuel cost and battery aging.

Future Automotive Systems Technology Simulator (FASTSim) is a free and open-source tool developed by National Renewable Energy Lab (NREL). Among the attractive capabilities of the FASTSim is that it can perform computationally efficient fuel economy simulations of automotive vehicles with reasonable accuracy for standard or arbitrary drive cycles. The modeling capability includes vehicles with various types of powertrains such as: conventional vehicles (CVs), hybrid-electric vehicles (HEVs), plugin hybrid electric vehicles (PHEVs) and battery-only electric vehicles (BEVs). The public version of FASTSim available from NREL is implemented in Excel, which achieves the goal of good accessibility to a broad audience, but has some limitations, including: i) bottleneck in computations when importing arbitrary drive cycles, ii) slower computations in general than other scripting or programming languages, and iii) less portable to integration with other applications and/or other platforms.

In order to reduce CO₂, Electric Vehicles (EV) and Hybrid Vehicles (HV) are effective. Those types of vehicles have powertrains from conventional vehicles. Those new powertrains drastically improve their efficiency from conventional vehicles keeping the same or superior power performance. On the other hand, those vehicles have an issue for thermal energy shortage during warming up process. The thermal energy is very large, and seriously affects the fuel economy for HV and the mileage for EV. In this paper, we propose VHDL-AMS multi-domain simulation technique for the estimation of the vehicle performance at the concept planning stage. The VHDL-AMS is IEEE and IEC standardized language, which supports not only multi-domain (physics) but also encryption. The common modeling language and encryption standard is indispensable for full-vehicle simulation.

In this paper, two correlations, Windowed Selected Moving Autocorrelation (WSMA) and Tri-Correlation (TriC), are introduced and discussed. The WSMA is simpler than the conventional autocorrelation. WSMA uses less data points to obtain useful signal content at desired frequencies. The computational requirement is therefore reduced compared to the conventional autocorrelation. The simplified TriC provides improved signal to noise separation capability than WSMA does while still requiring reduced computational effort compared to the standard autocorrelation. Very often, computation resource limitation exists for real-time applications. Therefore, the WSMA and TriC offer more opportunities for real-time monitor and feedback control applications in the frequency domain due to their high efficiencies. As an example, applications in internal combustion (IC) engine misfire detection are presented. Simulation and vehicle test results are also presented in this paper.

The paper describes an experimental activity on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel at engine-like conditions. The influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio) has been studied by spraying fuel in an optically-accessible constant-volume combustion vessel. A high-speed imaging system, capable of acquiring Mie-scattering and Schlieren images in a near simultaneous fashion mode along the same line of sight, has been developed at the Michigan Technological University using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies have been performed at three injection pressures (70, 120 and 180 MPa), 23.9 kg/m3 ambient gas density and 900 K gas temperature in the vessel.

This paper describes a new method to predict the rupture of spot welds, suitable for vehicle crash simulation. In a crash simulation used for vehicle development process, the calculation is performed assuming that the spot welds in the vehicle do not rupture. However, if some spot welds rupture in test of a prototype vehicle, the simulated deformation and test deformation may not match, resulting in inaccurate estimation of deformation from simulation. Therefore accuracy of predicting the rupture of spot welds is crucial in accurately estimating the deformation and improving reliability of vehicle crash simulation results. The new method to predict the rupture of spot welds which relates axial and shear forces and bending moment of spot weld to stress around nugget has been developed by authors. Based on developed method, the rupture risk of spot welds has been estimated. The new method was applied to estimate the spot weld rupture using three types of specimens.