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The die wear up to 80,800 hits on a prog-die setup for bare DP1180 steel was investigated in real production condition. In total, 31 die inserts with the combination of 11 die materials and 9 coatings were evaluated. The analytical results of die service life for each insert were provided by examining the evolution of surface wear on inserts and formed parts. The moments of appearance of die defects, propagation of die defects, and catastrophic failure were determined. Moreover, the surface roughness of the formed parts for each die insert was characterized using Wyko NT110 machine. The objectives of the current study are to evaluate the die durability of various tooling materials and coatings for flange operations on bare DP 1180 steel and update OEM tooling standards based on the experimental results. The current study provides the guidance for the die material and coating selections in large volume production for next generation AHSSs.

The introduction of new safety critical features using software-intensive systems presents a growing challenge to hazard analysis and requirements development. These systems are rich in feature content and can interact with other vehicle systems in complex ways, making the early development of proper requirements critical. Catching potential problems as early as possible is essential because the cost increases exponentially the longer problems remain undetected. However, in practice these problems are often subtle and can remain undetected until integration, testing, production, or even later, when the cost of fixing them is the highest. In this paper, a new technique is demonstrated to perform a hazard analysis in parallel with system and requirements development. The proposed model-based technique begins during early development when design uncertainty is highest and is refined iteratively as development progresses to drive the requirements and necessary design features.

To investigate the effect of aeration on fluid-elastomer compatibility, 4 types of elastomers were aged in three gear lubes. The four types of elastomers include a production fluorinated rubber (FKM) and production hydrogenated nitrile rubber (HNBR) mixed by the part fabricator, a standard low temperature flexible fluorinated rubber (FKM, ES-4) and a standard ethylene-acrylic copolymer (AEM, ES-7) mixed by SAE J2643 approved rubber mixer. The three gear lubes are Fluid a, Fluid b and Fluid c, where Fluid b is a modified Fluid with additional friction modifier, and Fluid c is friction modified chemistry from a different additive supplier. The aeration effect tests were performed at 125°C for 504 hours. The aerated fluid aging test was performed by introducing air into fluid aging tubes as described in General Motors Company Materials Specification GMW16445, Appendix B, side-by-side with a standard ASTM D471 test.

Determining Li-ion battery life through life modeling is an excellent tool in determining and estimating end-of-life performance. Achieving End-of-Life (EOL) can be challenging since it is difficult to achieve both cycle and calendar life during the same test without years of testing. The plan to correlate testing with the model included three (3) distinct temperature ranges, beginning with the four-Season temperature profile, an aggressive profile with temperatures in the 50 to 55°C range, and using a mid-temperature range (40-45°C) as a final comparison test. A high duty-cycle drive profile was used to cycle all of the batteries as quickly as possible to reach the one potential definition of EOL; significant increases in resistance or capacity fade.

FlexRay is a communication system targeted at, among other things, fault tolerant applications. In contrast to some other communication systems, FlexRay systems often contain a central device such as an active star. Due to their ability to isolate portions of the communication system central devices offer opportunities to mitigate certain faults. This paper presents several alternatives for the central device of a FlexRay system, specifically active stars, FlexRay switches, and Central Bus Guardians. The paper analyzes the fault detection, isolation and mitigation mechanisms of each central device based on available documentation and specifications.

Simscape is a physical modeling language developed by Mathworks Inc. The language uses equation statements instead of assignment statements to describe physical systems. The paper focuses on the Simscape language itself instead of using components in the Simscape libraries. The language will be introduced from a perspective different from the Mathworks' Physical Network point of view. Our perspective focuses on two types of variables at the connectors. In additional, internal variables are not separated into through and across variables. The alternative perspective is more general and easier to understand. The paper also illustrates how to develop components in a powertrain library following the proposed new perspective.

A Design for Six Sigma (DFSS) statistical approach is presented in this report to correlate a CFD cabin model with test results. The target is the volume-averaged hot-soak terminal temperature. The objective is to develop an effective correlation process for a simplified CFD cabin model so it can be used in practical design process. It is, however, not the objective in this report to develop the most accurate CFD cabin model that would be too expensive computationally at present to be used in routine design analysis. A 3-D CFD model of a vehicle cabin is the central part of the computer modeling in the development of automotive HVAC systems. Hot-soak terminal temperature is a thermal phenomenon in the cabin of a parked vehicle under the Sun when the overall heat transfer reaches equilibrium. It is often part of the simulation of HVAC system operation.

Today many vehicles are being developed with advanced computing and sensing technologies. These new technologies have contributed in enhancing driving safety and convenience. As an example, the Adaptive Cruise Control (ACC) can automatically adjust the vehicle speed to driver's set speed and maintain the driver-requested headway distance to the lead vehicle. In this paper, we further consider the automatic control of speed according to the road attributes, e.g., the speed limit and curve of the road. Two new features, ‘speed limit follower’ and ‘curve speed control’ algorithms, are proposed in this paper. These new features communicate with the conventional ACC system and control the vehicle speed while traveling across different curved roads and speed limit zones. These new features were developed as an independent function, so they can be integrated with any other existing ACC systems.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

Insulation coordination requirements for electrical equipment applications are defined in various standards. The standards are defined for application to stationary mains connected equipment, like IT, power supply or industrial equipment. Protection from an electric shock is considered the primary hazard in these standards. These standards have also been used in the design of various automotive components. IEC 60664-1 is an example of the standard. Automobiles are used across the world, in various environments and in varied usage by the customers. Automobiles need to consider possible additional hazards including electric shock. This paper will provide an overview of how to adapt these standards for automotive application in the design of High Voltage (HV) automotive components, including High Voltage batteries and other HV components connected to the battery. The basic definitions from the standards and the principles are applied for usage in automotive applications.

General Motors' (GM) eAssist powertrain builds upon the knowledge and experience gained from GM's first generation 36Volt Belt-Alternator-Starter (BAS) system introduced on the Saturn VUE Green Line in 2006. Extensive architectural trade studies were conducted to define the eAssist system. The resulting architecture delivers approximately three times the peak electric boost and regenerative braking capability of 36V BAS. Key elements include a water-cooled induction motor/generator (MG), an accessory drive with a coupled dual tensioner system, air cooled power electronics integrated with a 115V lithium-ion battery pack, a direct-injection 2.4 liter 4-cylinder gasoline engine, and a modified 6-speed automatic transmission. The torque-based control system of the eAssist powertrain was designed to be fully integrated with GM's corporate common electrical and controls architectures, enabling the potential for broad application across GM's global product portfolio.

Conventional HVAC systems adjust the position of a temperature door, to achieve a required air temperature discharged into the passenger compartment. Such systems are based upon the fact that a conventional (non-hybrid) vehicle's engine coolant temperature is controlled to a somewhat constant temperature, using an engine thermostat. Coolant flow rate through the cabin heater core varies as the engine speed changes. EREVs (Extended Range Electric Vehicles) & PHEVs (Plug-In Hybrid Electric Vehicles) have two key vehicle requirements: maximize EV (Electric Vehicle) range and maximize fuel economy when the engine is operating. In EV mode, there is no engine heat rejection and battery pack energy is consumed in order to provide heat to the passenger compartment, for windshield defrost/defog and occupant comfort. Energy consumption for cabin heating must be optimized, if one is to optimize vehicle EV range.

Electrification of the transportation industry is increasing rapidly with batteries currently the technology of choice. At the end of life, the battery chemistry used to electrify the vehicle may not be easily identifiable. A simple, common identifier is required to allow consumers, service and waste management personnel to direct unknown battery types to appropriate recyclers or secondary use markets. Recyclers also benefit from this identifier as it allows them to sort, screen for potential contamination to existing process streams, and identify the manufacturer so they may contact them to find detailed information about the battery to ensure proper and safe recycling. The SAE Battery Recycling Committee has recommended that batteries be identified by battery system, miscellaneous hazards and date of manufacture be identified as part of chemistry identification code. For the lithium-ion chemistry it is further recommended that cathode and anode be specified.

This work is to propose a new Iterative Learning Observer (ILO)-based strategy for State Of Charge (SOC) estimation. The ILO is able to estimate the SOC in real time while identifying modeling errors and/or disturbances at the same time. An Electrical-Circuit Model (ECM) is adopted to characterize the Lithium-ion battery behavior. The ILO is designed based on this ECM and the stability is proved. Several experiments are conducted and the collected data is used to extract ECM parameters. The effectiveness of the estimated SOCs via ILO is verified by the experimental results. This implies that the ILO-based SOC determination scheme is effective to identify the SOC in real time.

The urea injection is a key function in Urea-SCR NOx reduction system. As the tailpipe NOx emission standard becomes increasingly stringent, it is critical to diagnose the injection faults in order to guarantee the SCR DeNox functionality and performance. Particularly, a blocked injector may cause under-dosing of urea thus reduced DeNox functionality. Monitoring urea injection rate is one of the efficient methods for injection fault diagnosis. However, direct measurement of the urea mass flow is not feasible due to its high cost. This paper presents methods that are promising for detecting and isolating faults in urea injection by processing certain actuator signal and existing sensory measurements, e.g., the injector Pulse Amplitude Modulated (PAM) command and the pressure of the urea delivery line. No additional dedicated sensor is required. Three methods are discussed to detect urea injection system faults.

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.

With the introduction of plug-in electric vehicles (PEVs), the conventional mindset of “fill-up time” will be challenged as customers top off their battery packs. For example, using a standard 120VAC outlet, it may take over 10hrs to achieve 40-50 miles of EV range-making range anxiety a daunting reality for EV owners. As customers adapt to this new mindset of charge time, it is critical that automotive OEMs supply the consumer with accurate charge time estimates. Charge time accuracy relies on a variety of parameters: battery pack size, power source, electric vehicle supply equipment (EVSE), on-board charging equipment, ancillary controller loads, battery temperature, and ambient temperature. Furthermore, as the charging events may take hours, the initial conditions may vary throughout a plug-in charge (PIC). The goal of this paper is to characterize charging system sensitivities and promote best practices for charge time estimations.

Mid 2006 a study group at General Motors developed the concept for the electric vehicle with extended range (EREV),. The electric propulsion system should receive the electrical energy from a rechargeable energy storage system (RESS) and/or an auxiliary power unit (APU) which could either be a hydrogen fuel cell or an internal combustion engine (ICE) driven generator. The study result was the Chevrolet VOLT concept car in the North American Auto Show in Detroit in 2007. The paper describes the requirements, concepts, development and the performance of the battery used as RESS for the ICE type VOLTEC propulsion system version of the Chevrolet Volt. The key requirement for the RESS is to provide energy to drive an electric vehicle with “no compromised performance” for 40 miles. Extended Range Mode allows for this experience to continue beyond 40 miles.

The battery system in the Chevrolet Volt is very complex and must balance a variety of performance criteria, including the safety of vehicle occupants and other users. In order to assure a thorough approach to battery system safety, a system safety engineering process was applied and found to provide a useful framework. This methodical approach began with the preliminary hazard analysis and continued through requirements definition, design development and, finally, validation. Potentially hazardous conditions related directly to functional safety (for example, charge control) and primary physical safety (for example, short circuit conditions) can all be addressed in this manner. Typical battery abuse testing, as well as newly defined limit testing, supported the effort. Extensive documentation, traceability and peer reviews helped to verify that all issues were addressed.

Remote vehicle start systems are commonly available as an aftermarket accessory, and more recently, as a factory installed vehicle feature. These systems and their associated algorithms enable a user of the vehicle to remotely start the engine and/or other vehicle systems with the end goal of preconditioning the cabin environment, for example, if the user wishes to have the vehicle's interior heated or cooled before the user enters the vehicle. However, if the engine is remotely started for an extended period of time, the increased use of fuel, energy, and/or other resources may be greater than optimal or desired. Through the use of available vehicle sensors and enhanced algorithms, a system can be implemented which allows the passenger cabin to be heated or cooled to within a range of moderate temperatures, while reducing the resources utilized by the vehicle.