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Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

A dynamic computer model of automotive air conditioning systems was developed. The model uses simulation software for the coding of 1-D heat transfer, thermodynamics, fluid flow, and control valves. The same software is used to model 3-D solid dynamics associated with mechanical mechanisms of the compressor. The dynamics of the entire AC system is thus simulated within the same software environment. The results will show the models potential applications in component and system design, calibration and control.

Proper electric and thermal management of an HEV battery pack, consisting of many modules of cells, is imperative. During operation, voltage and temperature differences in the modules/cells can lead to electrical imbalances from module to module and decrease pack performance by as much as 25%. An active battery management system (BMS) is a must to monitor, control, and balance the pack. The University of Toledo, with funding from the U.S. Department of Energy and in collaboration with DaimlerChrysler and the National Renewable Energy Laboratory has developed a modular battery management system for HEVs. This modular unit is a 2nd generation system, as compared to a previous 1st generation centralized system. This 2nd generation prototype can balance a battery pack based on cell-to-cell measurements and active equalization. The system was designed to work with several battery types, including lithium ion, NiMH, or lead acid.

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

System integration is the path to successful entry of hybrid electric vehicle (HEV) technology into the marketplace. A modular solution capable of meeting varying customer requirements is needed. The controller must possess a flexible hierarchical architecture that insures cross-platform compatibility and provides adaptability for various engine, motor, transmission, and battery configurations. A hybrid powertrain supervisory controller (PSC) has been designed for an advanced parallel-type HEV prototype, which uses a continuously variable transmission (CVT). The controller schedules torque commands for the engine and motor and chooses the transmission ratio to meet driver demanded acceleration. The controller is organized around a state machine, which determines how best to employ powertrain components to satisfy the driver while maximizing fuel economy.

This paper gives an overview of a scalable engine management system architecture for motorcycle and other small engine based vehicle applications. The system can accommodate any engine sizes and up to four cylinders. The architecture incorporates advanced functionalities such as oxygen sensing, closed loop fueling, wall-wetting compensation, purge control, start & idle control and deceleration fuel cut-off. Additionally, a number of vehicle-related controls are integrated in the system. Diagnostic and safety related features have also been incorporated with limp-home capability. The software architecture is compatible with different hardware solutions. The system has been implemented in several OEM vehicles around the globe and meets EURO-3 emission requirements.

Battery second use-putting used plug-in electric vehicle (PEV) batteries into secondary service following their automotive tenure-has been proposed as a means to decrease the cost of PEVs while providing low cost energy storage to other fields (e.g., electric utility markets). To understand the value of used automotive batteries, however, we must first answer several key questions related to battery degradation, including: How long will PEV batteries last in automotive service? How healthy will PEV batteries be when they leave automotive service? How long will retired PEV batteries last in second-use service? How well can we best predict the second-use lifetime of a used automotive battery? Under the support of the U.S. Department of Energy's Vehicle Technologies Office, the National Renewable Energy Laboratory has developed a methodology and the requisite tools to answer these questions, including the Battery Lifetime Simulation Tool (BLAST).

In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations.

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage potential buyers. A subscription model in which a service provider owns the battery and supplies access to battery swapping infrastructure could reduce upfront and battery replacement costs with a predictable monthly fee, while expanding BEV range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, battery life, etc. The National Renewable Energy Laboratory has applied its Battery Ownership Model to compare the economics and utility of BEV battery swapping service plan options to more traditional direct ownership options.

Accelerated market penetration of plug-in electric vehicles (PEVs) is presently restricted by the high cost of batteries. Deployment of grid-connected energy storage, which could increase the reliability, efficiency, and cleanliness of the grid, is similarly inhibited by the cost of batteries. Research, development, and manufacturing are underway to reduce cost by lowering material costs, enhance process efficiencies, and increase production volumes. Another approach under consideration is to recover a fraction of the battery cost after the battery has been retired from vehicular service via reuse in other applications, where it may still have sufficient performance to meet the requirements of other energy-storage applications.

The purpose of this paper is to demonstrate our success in taking advantage of model-based development tools and auto-code technology to accelerate the typical life cycle development of powertrain software. In particular, we applied the technology as a clean sheet approach to Visteon's third generation Electronic Throttle Control system. In the process of applying model-based development and 100% auto-code, we identified various pitfalls and created solutions to overcome the gap between technology and development process during each phase of the entire software development life cycle. We will share our lessons learned during the requirement, design, implementation, and validation stages.

Fuel cell hybrid vehicles (FCHVs) use an energy management strategy to partition the power supplied by the fuel cell and energy storage system (ESS). This paper presents an adaptive energy management strategy, created in the ADVISOR™ software, for a series FCHV. The strategy uses a local or “real-time” optimization approach, which aims to reduce total energy consumption at each instantaneous time interval by dynamically adjusting the amount of power supplied by the fuel cell and ESS. Compared with a static control strategy, the adaptive strategy improved the simulated FCHV's fuel economy by 1.4%-8.5%, depending on the drive cycle.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

Traditionally fog lamps use halogen filament light sources. With the emergence of high brightness white LEDs, it is now possible to develop automotive forward lighting systems with LED light sources. Six LEDs are shown to be sufficient for the implementation of a European fog lamp using a faceted reflector optical approach. Each reflector together with the LED light source forms a modular element. The optical parameters of two different lamp designs are compared and correlation between the simulation and prototype measurements is shown. Further, additional forward lighting functions can be implemented through the use of additional elements.

Commonly, a significant event is detected when a normally stable engine parameter (ex. sensor voltage, sensor current, air flow, pedal position, fuel level, tire pressure, engine acceleration, etc.) transiently exceeds a calibrated detection threshold. Many implementations of detection thresholds rely on multi-input lookup tables or functions and are complex and difficult to calibrate. An approach is presented to minimize threshold calibration effort and complexity, while improving detection performance, by dynamically computing thresholds on-line based on current real-time data. Determining engine synchronization without a camshaft position sensor is presented as an illustrative application.

This paper discusses our experiences on the implementation and benefits of using the Hardware-In-the-Loop (HIL) systems for Powertrain control system software verification and validation. The Visteon HIL system integrated with several off-the-shelf diagnostics and calibration tools is briefly explained. Further, discussions on test automation sequence control and failure insertion are outlined The capabilities and advantages of using HIL for unit level software testing, open loop and closed-loop system testing, fault insertion and test automation are described. HIL also facilitates Software and Hardware Interface validation testing with low-level driver and platform software. This paper attempts to show the experiences with and capabilities of these HIL systems.

This paper describes the applicability of optical imaging techniques to the analysis of the scratch resistance of automotive interior plastic materials. The evaluation of so-called “finger testing” has traditionally relied upon human vision for detection of the initial scratch position. Commonly performed under uniform and defined illumination conditions, the relative contrast difference signified by whitening on a surface as determined by unaided human vision is a highly variable subjective perception; thus individual inspectors may determine the “whitening” point differently. This paper compares test data obtained from both visual and instrumental evaluation methods and discusses the advantages of optical imaging techniques for surface defect analysis.

Today’s electric vehicle (EV) owners charge their vehicles mostly at home and seldom use public direct current fast charger (DCFCs), reducing the need for a large deployment of DCFCs for private EV owners. However, due to the emerging interest among transportation network companies to operate EVs in their fleet, there is great potential for DCFCs to be highly utilized and become economically feasible in the future. This paper describes a heuristic algorithm to emulate operation of EVs within a hypothetical transportation network company fleet using a large global positioning system data set from Columbus, Ohio. DCFC requirements supporting operation of EVs are estimated using the Electric Vehicle Infrastructure Projection tool. Operation and installation costs were estimated using real-world data to assess the economic feasibility of the recommended fast charging stations.

Determination of the critical speed of a driveshaft is critical for development and validation of its design for use in a vehicle because of its destructive effects. Typical calculations to determine critical speed are either over simplistic and not very accurate or very complicated requiring CAE software and capabilities. An analytical five-section non-prismatic beam model was developed to fill in this gap. The model was developed to compute the critical speed in a worksheet and proven to be as or more accurate as utilizing FEA methods. The model worksheet calculates the critical speed for one-piece conventional driveshafts and adapted for Visteon's Slip-In-Tube (SIT) driveshafts.