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Technical Paper

A Simplified Battery Model for Hybrid Vehicle Technology Assessment

2007-04-16
2007-01-0301
The objective of this work is to provide a relatively simple battery energy storage and loss model that can be used for technology screening and design/sizing studies of hybrid electric vehicle powertrains. The model dynamic input requires only power demand from the battery terminals (either charging or discharging), and outputs internal battery losses, state-of-charge (SOC), and pack temperature. Measured data from a vehicle validates the model, which achieves reasonable accuracy for current levels up to 100 amps for the size battery tested. At higher current levels, the model tends to report a higher current than what is needed to create the same power level shown through the measured data. Therefore, this battery model is suitable for evaluating hybrid vehicle technology and energy use for part load drive cycles.
Technical Paper

A Target Cascading Method Using Model Based Simulation in Early Stage of Vehicle Development

2019-04-02
2019-01-0836
In the early stages of vehicle development, it is important for decision makers to understand a feasible constraint region that satisfies all system level requirements. The purpose of this paper is to propose a target cascading method to solve for a feasible design region which satisfies all constraints of the system based on model based simulation. In this method, the feasible design region is explored by using both global optimization methods and active learning techniques. In optimization problems, the inverse problem for understanding feasibility for specific designs is defined and solved. To determine the objective functions of the inverse problem, an index representing the achievement level of constraints from system requirements is introduced. To predict feasible regions in the specific design space, a surrogate model of minimized values of the index is trained by using a kriging model.
Journal Article

Admissible Shape Parameters for a Planar Quasi-Static Constraint Mode Tire Model

2017-08-17
2017-01-9683
Computationally efficient tire models are needed to meet the timing and accuracy demands of the iterative vehicle design process. Axisymmetric, circumferentially isotropic, planar, discretized models defined by their quasi-static constraint modes have been proposed that are parameterized by a single stiffness parameter and two shape parameters. These models predict the deformed shape independently from the overall tire stiffness and the forces acting on the tire, but the parameterization of these models is not well defined. This work develops an admissible domain of the shape parameters based on the deformation limitations of a physical tire, such that the tire stiffness properties cannot be negative, the deformed shape of the tire under quasi-static loading cannot be dominated by a single harmonic, and the low spatial frequency components must contribute more than higher frequency components to the overall tire shape.
Technical Paper

An Artificial Neural Network Model to Predict Tread Pattern-Related Tire Noise

2017-06-05
2017-01-1904
Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.
Technical Paper

An Extended-Range Electric Vehicle Control Strategy for Reducing Petroleum Energy Use and Well-to-Wheel Greenhouse Gas Emissions

2011-04-12
2011-01-0915
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).
Technical Paper

Analysis of Personal Routing Preference from Probe Data in Cloud

2020-04-14
2020-01-0740
Routing quality always dominates the top 20% of in vehicle- navigation customer complaints. In vehicle navigation routing engines do not customize results based on customer behavior. For example, some users prefer the quickest route while some prefer direct routes. This is because in vehicle navigation systems are traditionally embedded systems. Toyota announced that new model vehicles in JP, CN, US will be connected with routing function switching from the embedded device to the cloud in which there are plenty of probe data uploaded from the vehicles. Probe data makes it possible to analyze user preferences and customize routing profile for users. This paper describes a method to analyze the user preferences from the probe data uploaded to the cloud. The method includes data collection, the analysis model of route scoring and user profiling. Furthermore, the evaluation of the model will be introduced at the end of the paper.
Technical Paper

Animal-Vehicle Encounter Naturalistic Driving Data Collection and Photogrammetric Analysis

2016-04-05
2016-01-0124
Animal-vehicle collision (AVC) is a significant safety issue on American roads. Each year approximately 1.5 million AVCs occur in the U.S., the majority of them involving deer. The increasing use of cameras and radar on vehicles provides opportunities for prevention or mitigation of AVCs, particularly those involving deer or other large animals. Developers of such AVC avoidance/mitigation systems require information on the behavior of encountered animals, setting characteristics, and driver response in order to design effective countermeasures. As part of a larger study, naturalistic driving data were collected in high AVC incidence areas using 48 participant-owned vehicles equipped with data acquisition systems (DAS). Continuous driving data including forward video, location information, and vehicle kinematics were recorded. The respective 11TB dataset contains 35k trips covering 360K driving miles.
Technical Paper

Avoiding the Pitfalls in Motorsports Data Acquisition

2008-12-02
2008-01-2987
Restrictions on track testing, combined with advances in technology, have contributed to an increased dependence on sensors and data acquisition for diagnosing problems and improving performance in motorsports vehicles. This dependence has created a new set of challenges for race engineers to collect quality data from a vehicle at the track. Successful 7- or 8-post shaker rig testing is highly dependent on the quality of the data acquired at the track. An improperly configured data acquisition system can actually be worse than a faulty sensor. This paper highlights a few of the most common problems in motorsports data acquisition: aliasing and sample rate selection. The effects of these problems are described for typical suspension sensors such as accelerometers, shock potentiometers, load cells, and laser ride height sensors. An experimental case study is presented to explain the implications of these problems.
Journal Article

Battery Charge Balance and Correction Issues in Hybrid Electric Vehicles for Individual Phases of Certification Dynamometer Driving Cycles as Used in EPA Fuel Economy Label Calculations

2012-04-16
2012-01-1006
This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.
Technical Paper

CAE Methodology for Optimizing NVH, Functional Reliability, and Mass Reduction at Engine Concept Design Phase

2011-05-17
2011-01-1511
Due to the global economic downturn and higher environmental awareness, the social demands for low cost and fuel efficient vehicles are increasing. At the same time the engine power is increasing and customer expectations of reliability and NVH levels are increasing. To meet all the requirements, engineers are challenged to design light weight parts with higher performance. However, unconsidered mass reduction carries a risk of compromised NVH, Functional Reliability, and other functional demands. In order to resolve this contradiction, it is important to establish a basic structure with minimum necessary mass at the concept design phase, when there are still many degrees of freedom in the design space. Hence, a multi-objective optimization CAE methodology applicable for designing the basic structure of the Engine system was developed and is detailed below.
Technical Paper

CALVIN: Winner of the Fourth Annual Unmanned Ground Vehicle Design Competition

1997-02-24
970174
The Unmanned Ground Vehicle Competition is jointly sponsored by the SAE, the Association for Unmanned Vehicle Systems (AUVS), and Oakland University. College teams, composed of both undergraduate and graduate students, build autonomous vehicles that compete by navigating a 139 meter outdoor obstacle course. The course, which includes a sand pit and a ramp, is defined by painted continuous or dashed boundary lines on grass and pavement. The obstacles are arbitrarily placed, multi-colored plastic-wrapped hay bales. The vehicles must be between 0.9 and 2.7 meters long and less than 1.5 meters wide. They must be either electric-motor or combustion-engine driven and must carry a 9 kilogram payload. All computational power, sensing and control equipment must be carried on board the vehicle. The technologies employed are applicable in Intelligent Transportation Systems (ITS).
Technical Paper

Closed Loop Transaxle Synchronization Control Design

2010-04-12
2010-01-0817
This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.
Technical Paper

Coasting Technology for Real-World Fuel Economy Improvement of a Hybrid Vehicle

2020-04-14
2020-01-1195
Automobile manufactures need to adopt new technologies to meet global CO2 (carbon dioxide) emission regulations and better fuel efficiency demands from customers. Also, the production cost should be as low as possible for an affordable vehicle. Therefore, it is advantageous for OEMs to develop fuel efficient technologies which can be controlled by software without additional hardware costs. The coasting control is a fuel efficiency improvement technology that can be implemented by the change of vehicle software only. The coasting control is a technology that reduces the driving resistance (Deceleration) when the driver releases the gas pedal. This technology leads to reducing the energy required for the vehicle to drive and results in improving the real-world fuel economy. In an internal combustion engine (ICE) vehicle, the coasting state is achieved by changing the gear to neutral, and the effect has been discussed and clarified by many previous studies.
Technical Paper

Computational Design of Cathode Coating Materials for All-Solid-State Lithium-Ion Batteries

2021-04-06
2021-01-0758
All-solid-state lithium (Li)-ion batteries have attracted significant interest for their enhanced energy density compared with conventional batteries employing an organic liquid electrolyte. However, the interfacial impedance and reaction between electrodes and the electrolyte can hinder the transport of Li-ions, thus degrading the battery performance. This paper presents a systematic screening method to identify coatings to reduce impedance and maintain interface stability during battery operation. Promising coating materials are rapidly selected by evaluating properties for ideal coating materials from computational databases containing a vast collection of Li compounds. Finally, a few candidates are discovered and their battery performances are tested. This approach is demonstrated to be an efficient way to predict and evaluate functional coatings for a high performance all-solid -state battery design.
Technical Paper

Conceptual Design and Weight Optimization of Aircraft Power Systems with High-Peak Pulsed Power Loads

2016-09-20
2016-01-1986
The more electric aircraft (MEA) concept has gained popularity in recent years. As the main building blocks of advanced aircraft power systems, multi-converter power electronic systems have advantages in reliability, efficiency and weight reduction. The pulsed power load has been increasingly adopted--especially in military applications--and has demonstrated highly nonlinear characteristics. Consequently, more design effort needs to be placed on power conversion units and energy storage systems dealing with this challenging mission profile: when the load is on, a large amount of power is fed from the power supply system, and this is followed by periods of low power consumption, during which time the energy storage devices get charged. Thus, in order to maintain the weight advantage of MEA and to keep the normal functionality of the aircraft power system in the presence of a high-peak pulsed power load, this paper proposes a novel multidisciplinary weight optimization technique.
Technical Paper

Control Strategy Development for Parallel Plug-In Hybrid Electric Vehicle Using Fuzzy Control Logic

2016-10-17
2016-01-2222
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently developing a control strategy for a parallel plug-in hybrid electric vehicle (PHEV). The hybrid powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. Fuzzy rule sets determine the torque split between the motor and the engine using the accelerator pedal position, vehicle speed and state of charge (SOC) as the input variables. The torque producing components are a 280 kW V8 L83 engine with active fuel management (AFM) and a post-transmission (P3) 100 kW custom motor. The vehicle operates in charge depleting (CD) and charge sustaining (CS) modes. In CD mode, the model drives as an electric vehicle (EV) and depletes the battery pack till a lower state of charge threshold is reached. Then CS operation begins, and driver demand is supplied by the engine operating in V8 or AFM modes with supplemental or loading torque from the P3 motor.
Technical Paper

Deployment of OTA-Upgradable Teammate Advanced Drive

2022-03-29
2022-01-0063
Teammate Advanced Drive is a driving support system with state-of-the-art automated driving technology that has been developed for customers’ safe and secure driving on highways based on the Toyota’s Mobility Teammate Concept. This SAE Level 2 (L2) system assists overtaking, lane changes, and branching to the destination, in addition to providing hands-free lane centering and car following. The automated driving technology includes self-localization onto a High Definition Map, multi-modal sensing to cover 360 degrees of the surrounding environment using fusion of LiDARs, cameras, and radars, and a redundant architecture to realize fail-safe operation when a malfunction or system limitation occurs. High-performance computing is provided to implement deep learning for predicting and responding to various situations that may be encountered while driving.
Technical Paper

Developing a Compact Continuous-State Markov Chain for Terrain Road Profiles

2013-04-08
2013-01-0629
Accurate terrain models provide the chassis designer with a powerful tool to make informed design decisions early in the design process. It is beneficial to characterize the terrain as a stochastic process, allowing limitless amounts of synthetic terrain to be created from a small number of parameters. A continuous-state Markov chain is proposed as an alternative to the traditional discrete-state chain currently used in terrain modeling practice. For discrete-state chains, the profile transitions are quantized then characterized by a transition matrix (with many values). In contrast, the transition function of a continuous-state chain represents the probability density of transitioning between any two states in the continuum of terrain heights. The transition function developed in this work uses a location-scale distribution with polynomials modeling the parameters as functions of the current state.
Technical Paper

Development & Integration of a Charge Sustaining Control Strategy for a Series-Parallel Plug-In Hybrid Electric Vehicle

2014-10-13
2014-01-2905
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP), HEVT is designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle.
Journal Article

Development Progress of the Toyota Fuel Cell Hybrid Vehicle

2008-04-14
2008-01-0420
Since 1992, Toyota Motor Corporation (TMC) has been working on the development of fuel cell system technology. TMC is designing principal components in-house, including fuel cell stacks, high-pressure hydrogen storage tank systems, and hybrid systems. TMC developed the '02 model TOYOTA FCHV, the world-first market-ready fuel cell vehicle, and started limited lease of the vehicles in 2002. In 2005, TMC developed a new model of TOYOTA FCHV which obtained vehicle type certification in Japan, and is currently available for leasing. TMC has improved the cruising range and cold start/drive capability of the TOYOTA FCHV, and conducted public road tests to evaluate the performance. The improved TOYOTA FCHV successfully traveled from Osaka to Tokyo (approximately 560km, 350 miles) on a single fueling of hydrogen. In addition, the cold weather tests carried out in Hokkaido and North America have verified its starting/driving capability at subfreezing temperatures including -37°C.
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