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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 the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

This research examined driver acceptance and behavior associated with Speed Limit and Curve Advisor systems, including influences on speed choice. Drivers experienced messages from an emulated Speed Limit and Curve Advisor system during a 2-hour public road drive. Driver tolerance for system errors and message conflicts was also studied by manipulating the accuracy of the information provided by the system. Messages were presented using either a Head-Up Display or on an in-dash Driver Information Center. Results indicate that drivers liked having speed limit information continuously available to them while driving, but the information provided by the Speed Limit Advisor did not significantly influence or alter drivers' speed choice or deceleration profiles in comparison to driving without the system.

An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

Alternative implementations of a Rear Cross Traffic Alert (RCTA) system intended to actively notify drivers of the presence of rear cross-path traffic when backing were evaluated in naturalistic settings. The feature is one of several emerging technologies designed to assist drivers when backing - in this case, enhancing drivers' awareness of traffic approaching from the rear. The study allowed performance under a range of RCTA system driver interface implementations to be contrasted with conventional and wide Field of View (FOV) Rear Vision systems. Evaluations were conducted using a sample of 70 drivers under naturalistic settings and environments with repeated exposures to backing tasks. The study also made use of a staged conflict situation with a confederate vehicle in order to more precisely quantify driver behavior and system usage across drivers under controlled conflict situations.

Vehicle-to-vehicle (V2V) communication systems can enable a number of wireless-based vehicle features that can improve traffic safety, driver convenience, and roadway efficiency and facilitate many types of in-vehicle services. These systems have an extended communication range that can provide drivers with information about the position and movements of nearby V2Vequipped vehicles. Using this technology, these vehicles are able to communicate roadway events that are beyond the driver's view and provide advisory information that will aid drivers in avoiding collisions or congestion ahead. Given a typical communication range of 300 meters, drivers can potentially receive information well in advance of their arrival to a particular location. The timing and nature of presenting V2V information to the driver will vary depending on the nature and criticality of the scenario.

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 the rising cost of gasoline causing the adoption of the electric car into the lives of average consumers, new avenues of transportation cost control and consumer-vehicle interaction can be explored. Unlike a conventional ICE vehicle where a consumer cannot control the cost of what he or she pays for the fuel source, an electric vehicle provides a means for the consumer to directly impact the price for which they “fill-up”. GM's Programmable Charging feature offers a way for consumers to work directly with the power company to charge their electric vehicles during the most cost efficient hours. The consumer has the option to either start charging when plugging in the vehicle or utilizing the Programmable Charging feature to select a lower cost time to charge their vehicle's battery. Utilizing this feature also benefits the power companies by reducing demand on the Grid during peak usage hours when a customer would typically be charging her vehicle.

This paper examines Smart Electric Power Management as it pertains to when the vehicle charging system is active. Over the past decade there have been several factors at play which have stressed the demands placed upon the vehicle electrical power system. Many of these factors present challenges to electrical power that are at cross-purposes with one another. For example, demands of new and existing electrical loads, customer expectations about load performance and battery life, and the push by governments' world-wide for increased fuel economy (FE) and reduced CO2 emissions all have direct impact and can be directly impacted by decisions made in electric power design. As the electrification of the vehicle has progressed we now have much more specific vehicle state data available and the means to share this information among on-board computers through serial data link connectivity.

General Motors (GM) and the Virginia Tech Transportation Institute (VTTI) have partnered to conduct a series of studies characterizing the use and effectiveness of technologies designed to assist drivers while backing. A major emphasis of this research has been on Rear Vision Camera (RVC) systems that provide drivers with an enhanced view of the area behind the vehicle. RVC systems are intended to aid in positioning the vehicle when executing low-speed parking and backing-related tasks and are not necessarily well suited for detecting unexpected in-path obstacles (particularly if the RVC image is not coupled with object detection alerts issued to the driver).

Research was conducted to assess driver acceptance and performance associated with a spotter mirror feature intended to reduce the incidence of lane-change conflicts by enhancing drivers' ability to detect vehicles in their side blind zone. The spotter mirror consisted of an integrated spherical convex blind zone mirror inset within a larger planar mirror. The spotter mirror's field-of-view was designed to target the vehicle's side blind zone area and to help drivers quickly detect the presence or absence of a vehicle in the blind zone. The study captured normative lane-change behavior during an extended drive on public roadways, with and without access to the spotter mirror system, for a sample of familiar and unfamiliar supplemental mirror users. In order to capture more naturalistic lane-change behavior, drivers were informed that the purpose of the study was to evaluate the adequacy of existing road signs for navigating to a destination.

Internally excited torsional steering wheel vibrations at frequencies near 8-22 Hz on smooth roads can produce driver disturbances, commonly described as “SHAKE”. These vibrations are primarily excited by the rotating front suspension corners and are periodic in the rotational frequencies of the tire-wheel assemblies. The combination of vehicular dynamic amplification originating in dominant suspension and steering system vibratory modes, and a sufficiently large 1st harmonic non-uniformity excitation of the rotating corner components, can result in periodic vibrations exceeding thresholds of disturbance. Controlling the periodic non-uniformity excitation through individual component requirements (e.g., wheel imbalance, tire force variation, wheel runout, concentric piloting of wheel on hub) is difficult since the desired upper limits of individual component requirements for vibration-free performance are typically beyond industry capability.

In order to assess the possible ways of energy transfer from the various sources of excitation in a vehicle assembly to a given target location, frequency based substructuring technique and transfer path analysis are used. These methods help to locate the most important energy transfer paths for a specific problem, and to evaluate their individual effects on the target, thus providing valuable insight into the mechanisms responsible for the problem. The Source-Path-Receiver concept is used. The sources can be from the road surface, engine, transmission, transfer case, prop-shaft, differential, rotating components, chain drives, pumps, etc., and the receiver can be driver/passenger ears, steering column, seats, etc. This paper is devoted to identify the noise transfer paths and the force transmissibility among the interfaces of different components in the vehicle for the low to mid frequency range.

The plug-in vehicles developed in the 1990's ushered in the first standards for electrified vehicles. These standards included requirements for Electric Vehicle Supply Equipment or EVSEs. EVSE is a general term for all the non vehicle components needed to charge a plug-in vehicle. These components include cabling, connectors and shock safety equipment. EVSEs are used to charge vehicles at home, work and in commercial settings. Many people identify EVSEs with public charge stations. While public charge stations are iconic with plug-in vehicles, these are just one type of EVSE. Until public EVSEs become readily available, plug-in vehicle drivers will need to partially rely on portable versions of EVSE. Portable EVSEs are required to provide the identical function and safety protection as their stationary cousins but their portability brings unique challenges and design considerations.

An Extended Range Electric vehicle brings a wealth of new features since it is capable of driving on battery alone, has a range extending engine, and has a high voltage battery pack that can be recharged by plugging into wall power. The customer is able to interact with the vehicle's plug-in charging system through mobile applications. Along with all these new features is the challenge of designing a driver interface to provide important information to the customer. This paper will describe the unique customer interface features added to the vehicle, and will include some additional specifics related to the hardware used to provide the information.

As the auto industry becomes more dependent upon Electric Vehicles (Plug-In Hybrid Electric Vehicles, Battery Electric Vehicles, and Extended Range Electric Vehicles), the Plug-In Charging Feature will become an integral part of the driver's daily routine. The Plug-In Charging feature enables off-board electrical power grid (grid based) power to be used immediately or at a later time by on-vehicle functions. The primary use of this grid power is to charge the vehicle's High Voltage (HV) battery, but other uses also do exist. These functions will mainly be active when the vehicle is off.

In this paper we discuss the use of a formal approach to the problem of describing, evaluating, and specifying human-machine interaction. The statecharts language, originally conceived by David Harel [1], is used to describe the behavior of the machine (i.e., its states and transitions), interface indications (e.g., light indicators on switches), and user interaction (selecting applications, switching modes, entering parameters, etc.). We illustrate how the statecharts language can be used to describe driver interaction with a climate control system, and show how it is possible to systematically evaluate user interaction. The paper concludes with several observations about the utility of formal language for generating sound design specification of human-machine systems.

Extended Range Electric Vehicles (EREVs), which are Off board charging capable Electric Vehicles (EV) with an on board charging generator, rely on very complex Rechargeable Energy Storage Systems (RESS) and High Voltage (HV) distribution systems to enable operation as both an EV and an EREV. The connect feature manages the connection and disconnection of a High Voltage (HV) Rechargeable Energy Storage System (RESS) to and from the high voltage components in the vehicle. The RESS is connected to the vehicle's high voltage system to enable vehicle operation. The HV connect feature is a part of occupant, service personnel and first responder safety for all General Motors vehicles that contain high voltage systems. Implementation of the connect feature is the method deployed in GM vehicles to meet high voltage FMVSS requirements.

The number of adjustable vehicle interior components features is growing. For example, the number of adjustable components of a vehicle seat has been growing from 4-way to as many as 22-way. The presented study aims to develop understanding on how sensitive drivers and front passengers are to individual component adjustment of vehicle interior features. This understanding could provide insights on which adjustable vehicle interior components features are more important to be precisely adjusted. A commercially available full-size sedan, equipped with a 4-way adjustable steering column & wheel and an 8-way adjustable seat for drivers, and an 8-way adjustable seat for front passengers, was used in this study. A total of 29 and 30 consumers were participating in this study to adjust components to their comfort on driver and front passenger sides, respectively.

In recent years, there has been a growing interest in driver visibility. This is, in part, due to increasing emphasis placed on design factors influencing visibility such as: aerodynamics, styling, structural stiffness and vehicle packaging. During the development process of a vehicle, it is important to be able to quantify all of these factors. Visibility, however, owing to its sensory nature, has been harder to quantify. As a result, General Motors (GM) has undertaken a study to gain deeper insight into customer perceptions surrounding visibility. Clinics were conducted to help determine the relative importance of different metrics. The paper also explores several new metrics that can help predict customer satisfaction based on vehicle configuration.