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Plug-In Hybrid and Extended Range Electric Vehicle's have quickly become the focus of many OEM's and suppliers. Existing regulations and test procedures did not anticipate this rapid adoption of this new technology, resulting in many product development challenges. The lack of clear requirements is further complicated by CARBs consideration of CO2 inclusion in their next light duty OBD regulation. This presentation provides an overview of the regulatory requirements for OBD systems on hybrid vehicles that intend to certify in California. Near term challenges for EREV?s and PHEV?s are discussed, including concerns with the existing denominator and warm-up cycle calculations. Some proposals are made to address these concerns. Presenter Andrew Zettel, General Motors Company

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.

As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

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.

Three different acoustic finite element models of an automobile passenger compartment are developed and experimentally assessed. The three different models are a traditional model, an improved model, and an optimized model. The traditional model represents the passenger and trunk compartment cavities and the coupling between them through the rear seat cavity. The improved model includes traditional acoustic models of the passenger and trunk compartments, as well as equivalent-acoustic finite element models of the front and rear seats, parcel shelf, door volumes, instrument panel, and trunk wheel well volume. An optimized version of the improved acoustic model is developed by modifying the equivalent-acoustic properties. Modal analysis tests of a vehicle were conducted using loudspeaker excitation to identify the compartment cavity modes and sound pressure response to 500 Hz to assess the accuracy of the acoustic models.

Understanding the flow characteristics and, especially, how the aerodynamic forces are influenced by the changes in the vehicle body shape, are very important in order to improve vehicle aerodynamics. One specific goal of aerodynamic shape optimization is to predict the local shape sensitivities for aerodynamic forces. The availability of a reliable and efficient sensitivity analysis method will help to reduce the number of design iterations and the aerodynamic development costs. Among various shape optimization methods, the Adjoint Method has received much attention as an efficient sensitivity analysis method for aerodynamic shape optimization because it allows the computation of sensitivity information for a large number of shape parameters simultaneously.

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium-size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

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.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

With deflected-disc dampers, digressive force-velocity shapes are achieved via the combined effects of disc stack stiffness and hub-offset. The degree of digressiveness can be adjusted to alter vehicle performance by changing the proportion of these parameters. Optimizing this relationship can yield substantial vehicle performance improvements, but the time consuming iterative process of developing a new disc stack for each hub-offset discourages experimentation. To enable more efficient digressiveness comparisons, a regression-based computational method has been developed which converts disc stack stiffness from one hub-offset to other offsets directly, without iteration. Once an initial disc stack for one offset has been tuned by traditional methods, stacks for other offsets can be calculated that maintain overall damper control.

In 2006, the Insurance Institute for Highway Safety (IIHS) released a new Low Speed Bumper Test Protocol for passenger cars1. The new test protocol included the development of a deformable barrier that the vehicle would impact at low speeds. IIHS positioned the new barrier to improve correlation to low speed collisions in the field, and also to assess the ability of the bumper system to protect the vehicle from damage. The bumper system must stay engaged to the barrier to protect other vehicle components from damage. The challenge is to identify the bumper system design features that minimize additional cost and mass to keep engagement to the barrier. The results of the Design for Six Sigma analysis identified the design features that increase the stiffness of the bumper system enable it to stay engaged to the barrier and reduce the deflection.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

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.

Key fobs, also known as remote keys or remote transmitters, have become a common piece of equipment in today's vehicle, being ubiquitous in every market segment. Once limited to remote locking and unlocking operations, today's key fobs can be used to control many comfort and security features beyond locking and unlocking, such as alarm system operation, vehicle locate, approach lighting, memory seat recall, and remote starting systems. Key fobs are designed to be easy to use as well as easy to carry and transport in personal containers, such as purses, pockets, wallets, and the like. Accordingly, as with other personal effects, key fobs and other portable remote devices can be lost or misplaced or can be otherwise difficult to find. Even with careful tracking of a remote device, children and pets, among other factors, can make location difficult. Moreover, multiple remote devices are often distributed with each vehicle.

Small electric DC (Direct Current) motors used to actuate various mechanisms in vehicles have failed prematurely when exposed to some formulations of lubricants, which leached into the motor and caused shorting. The subject study explored this failure mechanism in detail as evidenced in vehicle power door lock actuators. Experiments were conducted through the application of various types of lubricants to motors in varying ways to re-create the failure mode experienced by the authors, and to determine an optimized selection of lubricant for maximized cycle life, robust to inherent component manufacturing process variation in both the amount and location of lubrication placement. The detailed data, photographs and conclusions which resulted were summarized. The electric motor failure mode experienced in the example situation was first explained and illustrated with detailed photography.

This study documents a method developed for dynamically measuring occupant pocketing during various low-speed rear impact, or “whiplash” sled tests. This dynamic pocketing measurement can then be related to the various test parameters used to establish the performance rating or compliance results. Consumer metric and regulatory tests discussed within this paper as potential applications of this technique include, but are not limited to, the Insurance Institute for Highway Safety (IIHS) Low Speed Rear Impact (LSRI) rating, Federal Motor Vehicle Safety Standard (FMVSS) 202a, and European New Car Assessment Program (EURO-NCAP) whiplash rating. Example metrics are also described which may be used to assist in establishing the design position of the head restraint and optimize the balance between low-speed rear impact performance and customer comfort.

For decades, the industry standard for laboratory durability simulations has been based on reproducing quantified vehicle responses. That is, build a running vehicle, measure its responses over a variety of durability road surfaces and reproduce those responses in the laboratory for durability evaluation. To bring a vehicle to market quickly, the time between tightening the last bolt on a prototype test vehicle and starting the durability evaluation test must be minimized. A method to derive 4-Post simulator displacements without measuring or predicting vehicle responses is presented.

Engineering has continuously strived to improve the vehicle development process to achieve high quality designs and quick to launch products. The design process has to have the tools and capabilities to help ensure both quick to the market product and a flawless launch. To achieve high fidelity and robust design, mistakes and other quality issues must be addressed early in the engineering process. One way to detect problems early is to use the math based modeling and simulation techniques of the analysis group. The correlation of the actual vehicle performance to the predictive model is crucial to obtain. Without high correlation, the change management process begins to get complicated and costs start to increase exponentially. It is critical to reduce and eliminate the risk in a design up front before tooling begins to kick off. The push to help achieve a high rate of correlation has been initiated by engineering management, seeing this as an asset to the business.