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Inside an automobile, hundreds of connectors and electrical terminals in various locations experience different corrosive environments. These connectors and electrical terminals need to be corrosion-proof and provide a good electrical contact for a vehicle’s lifetime. Saltwater and sulfuric acid are some of the main corrosion concerns for these electrical terminals. Currently, various thin metallic layers such as gold (Au), silver (Ag), or tin (Sn) are plated with a nickel (Ni) layer on copper alloy (Cu) terminals to ensure reliable electrical conduction during service. Graphene due to its excellent chemical stability can serve as a corrosion protective layer and prevent electrochemical oxidation of metallic terminals. In this work, effects of thin graphene layers grown by plasma-enhanced chemical vapor deposition (PECVD) on Au and Ag terminals and thin-film devices were investigated. Various mechanical, thermal/humidity, and electrical tests were performed.

A series of cold start experiments using a 2.0 liter gasoline turbocharged direct injection (GTDI) engine with custom controls and calibration were carried out using gasoline and iso-pentane fuels, to obtain the cold start emissions profiles for the first 5 firing cycles at an ambient temperature of 22°C. The exhaust gases, both emitted during the cold start firing and emitted during the cranking process right after the firing, were captured, and unburned hydrocarbon emissions (HC), CO, and CO2 on a cycle-by-cycle basis during an engine cold start were analyzed and quantified. The HCs emitted during gasoline-fueled cold starts was found to reduce significantly as the engine cycle increased, while CO and CO2 emissions were found to stay consistent for each cycle. Crankcase ventilation into the intake manifold through the positive-crankcase ventilation (PCV) valve system was found to have little effect on the emissions results.

Laser welding of the magnesium-bearing AA5xxx aluminum alloys is often beset by keyhole instability, especially in the lap through joint configuration. This phenomenon is characterized by periodic collapse of the keyhole leaving large voids in the weld zone. In addition, the top surface can exhibit undercut and roughness. In full penetration welds, keyhole instability can also produce a spikey root and severe top surface concavity. These discontinuities could prevent a weld from achieving engineering specification compliance, pose a craftsmanship concern, or reduce the strength and fatigue performance of the weld. In the case of a full penetration weld, a spikey root could compromise part fit-up and corrosion protection, or damage adjacent sheet metal, wiring, interior components, or trim.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

Computational Fluid Dynamic (CFD) analysis was performed using FLUENT to analyze the fluid thermal performance of a Battery cell container for the Ford Fusion Hybrid Electric Vehicle. The objective of the design was to maintain the cells in their desired operating temperature range with a near uniform temperature among the battery cells in the container, while minimizing energy losses associated with the pressure drop. Groupings of multiple such containers were assembled for bench test confirmation. Excellent agreement was obtained for air side pressure drop between the CFD and hardware physical properties. Multiple design iterations were made to improve the baseline design. Ultimately, the thermal gradient within the physical property was reduced to 1.8°C with a minimal increase in system pressure drop.

Thermal modeling of liquid-cooled vehicle traction battery assemblies using Computational Fluid Dynamics (CFD) usually involves large models to accurately resolve small cooling channel details, and intensive computation to simulate drive-cycle transient solutions. This paper proposes a segregated method to divide the system into three parts: the cells, the cold plate and the interface between them. Each of the three parts can be separated and thermally characterized and then combined to predict the overall system thermal behavior for both steady-state and transient operating conditions. The method largely simplifies battery thermal analysis to overcome the limitations of using large 3D CFD models especially for pack level dynamic drive cycle simulations.

Lithium-ion batteries (LIBs) have been used as the main power source for Electric vehicles (EVs) in recent years. The mechanical behavior of LIBs subject to crush loading is crucial in assessing and improving the impact safety of battery systems and EVs. In this work, a detailed 3D finite element model for a commercial vehicle battery was built, in order to better understand battery failure behavior under various loading conditions. The model included the major components of a prismatic battery jellyroll, i.e., cathodes, anodes, and separators. The models for these components were validated against the corresponding material coupon tests (e.g., tension and compression). Then the components were integrated into the cell level model for simulation of jellyroll loading and damage behavior under three types of compressive indenter loading: (1) Flat-end punch, (2) Hemispherical punch and (3) Round-edge wedge. The comparisons showed reasonable agreement between modeling and experiments.

Vehicle fire investigators sometimes use the existence and location of thermally damaged wiring (arced, shorted, melted, & beaded) discovered in a post burn analysis of a vehicle as an indication of the fire origin and its cause. One systematic method of analysis is to use the process of arc mapping. To examine the reliability of arc mapping in motor vehicle fires, two full scale burn demonstrations were conducted on 2013 Ford Fusions. Both vehicles had similar fire origins artificially initiated in the interior of the vehicles near the driver’s front seat. The engines were running and all accessories were off. During the burn sequence, occurrences of fire induced unintended electrical activity were captured with video and still photography. Examples of this unintended activity include lights, horn, wipers, and decklid latch activation. The burn concluded when the measured battery voltage went to zero in demonstration 1.

SAE standards require the function of a Manual Service Disconnect (MSD), when open, to remove any voltage between positive and negative Rechargeable Energy Storage System (RESS) output terminals. Another SAE standard specifies that measured voltage across all external battery terminal sets shall be less than 60 VDC within 5 seconds after the manual disconnect is actuated with the automatic disconnect (e.g., contactors) closed. In this paper, the location of the manual service disconnect is reviewed to meet isolation requirement of the battery pack system (i.e., RESS). Battery architectures with manual service disconnect located at the most positive side, most negative side, and center of the array or the pack were studied. Voltage measurement points and single point failure modes were considered. It was found that MSD location for a single contactor pack is most effective in reducing voltage potential at the terminals when placed on the other side of the contactor.

This paper, written in collaboration with Ford, evaluates the effectiveness of higher cell density combined with higher porosity, lower thermal mass substrates for emission control capability on a customized, RDE (Real Driving Emissions)-type of test cycle run on a chassis dynamometer using a gasoline passenger car fitted with a three-way catalyst (TWC) system. Cold-start emissions contribute most of the emissions control challenge, especially in the case of a very rigorous cold-start. The majority of tailpipe emissions occur during the first 30 seconds of the drive cycle. For the early engine startup phase, higher porosity substrates are developed as one part of the solution. In addition, further emission improvement is expected by increasing the specific surface area (GSA) of the substrate. This test was designed specifically to stress the cold start performance of the catalyst by using a short, 5 second idle time preceding an aggressive, high exhaust mass flowrate drive cycle.

This article aims to analyze the potential economic effects for consumers with the implementation of the Vehicle-to-Grid (V2G) and the Vehicle-to-Home (V2H) networks in Brazil. Nowdays, the usage of both technologies in Brazil are at a regulatory vacuum for both Battery Electric Vehicles (BEVs), Plug-in Hybrid Electric Vehicles (PHEVs) and Hybrid Electric Vehicles (HEVs). Usually, when a legislation lack occurs, the local OEMs adopt IECs (International Electrotechnical Commissions) and/or SAEs (Society of Automotive Engineers) reference international standards, such as SAE J1634 for range test.

Electrified vehicles including Battery Electric Vehicles (BEVs) and Plug-In Hybrid Vehicles (PHEVs) made by Ford Motor Company are fitted with a telematics modem to provide customers with the means to communicate with their vehicles and, at the same time, receive insight on their vehicle usage. These services are provided through the “MyFordMobile” website and phone applications, simultaneously collecting information from the vehicle for different event triggers. In this work, we study this data by using Big Data Methodologies including a Hadoop Database for storing data and HiveQL, Pig Latin and Python scripts to perform analytics. We present electrified vehicle customer behaviors including geographical distribution, trip distances, and daily distances and compare these to the Atlanta Regional Survey data. We discuss customer behaviors pertinent to electrified vehicles including charger types used, charging occurrence, charger plug-in times etc.

Mechanical shock tests for lithium metal and lithium-ion batteries often require that each cell or battery pack be subjected to multiple shocks in the positive and negative directions, of three mutually perpendicular orientations. This paper focuses on the no-disassembly requirement of those testing conditions and on the CAE methodology specifically developed to perform this assessment. Ford Motor Company developed a CAE analysis method to simulate this type of test and assess the possibility of cell dislodging. This CAE method helps identify and diagnose potential failure modes, thus guiding the Design Team in developing a strategy to meet the required performance under shock test loads. The final CAE-driven design focuses on the structural requirement and optimization, and leads to cost savings without compromising cell or pack mechanical performance.

As electric vehicles are becoming increasingly popular and necessary for the future mobility needs of civilization, further effort is continually made to improve the efficiency, cost, and safety of the lithium-ion battery packs that power these vehicles. To facilitate these goals, this paper introduces a data driven model to predict a distribution of surface temperatures for a lithium-ion battery pack: a long short-term memory (LSTM) neural network. The LSTM model is trained and validated with lithium-ion cells electrically connected to form a battery pack. Voltage, current, state of charge (SOC), and cell surface temperature from two arrays are used as inputs from a wide range of high and low temperature drive cycles. Additionally, ambient temperature is added as an input to the LSTM model.

Future lunar missions will utilize a Lunar DC microgrid (LDCMG) to construct the infrastructure for distributing, storing, and utilizing electrical energy. The LDCMG’s energy management, of which energy storage systems (ESS) are crucial components, will be essential to the success of the missions. Standard system design currently employs a rule-of-thumb approach in which design methodologies rely on heuristics that may only evaluate local power balancing requirements. The Hamiltonian surface shaping and power flow control (HSSPFC) method can also be utilized to analyze and design the lunar LDCMG power distribution network and ESS. In this research, the HSSPFC method will be utilized to determine the ideal energy storage requirements for ESS and the optimally distributed control architecture.

Real-world second-by-second vehicle driving cycle data is very important for vehicle research and development. A project solely dedicated to generating such information would be tremendously costly and time consuming. Alternatively, we developed such a database by utilizing two publicly available passenger vehicle travel surveys: 2004-2006 Puget Sound Regional Council (PSRC) Travel Survey and 2011 Atlanta Regional Commission (ARC) Travel Survey. The surveys complement each other - the former is in low time resolution but covers driver operation for over one year whereas the latter is in high time resolution but represents only one-week-long driving operation. After analyzing the PSRC survey, we chose 382 vehicles, each of which continuously operated for one year, and matched their trips to all the ARC trips. The matching is carried out based on trip distance first, then on average speed, and finally on duration.