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Lithium-ion batteries (LIBs) have been widely used as the energy storage system in plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) due to their high power and energy density and long cycle life compared to other chemistries. However, LIBs are sensitive to operating conditions, including temperature, current demand and surface pressure of the cell. One very well understood phenomenon of lithium-ion battery is the reduction in charge capacity over time due to cycling and storage commonly known as capacity fade. Considering the need for predicting the behavior of an aged cell and the need for estimating battery useful life for warranty purpose, it is crucial to predict the capacity fade with reasonable accuracy. To accommodate this need, a novel cell level empirical aging model is built based on storage tests and cycle tests. The storage test captures the calendar aging of the lithium-ion cell while the cycle test estimates the cycle aging of the cell.

Worldwide projections anticipate a fast-growing market share of the battery electric vehicles (BEVs) to meet stringent emissions regulations for global warming and climate change. One of the new challenges of BEVs is the effective and efficient thermal management of the BEV to minimize parasitic power consumption and to maximize driving range. Typically, the total efficiency of BEVs depends on the performance and power consumption of the thermal management system, which is highly affected by several factors, including driving environments (ambient temperature and traffic conditions) and driver's behavior (aggressiveness). Therefore, this paper investigates the influence of these factors on energy consumption by using a comprehensive BEV simulation integrated with a thermal management system model. The vehicle model was validated with experimental data, and a simulation study is performed by using the vehicle model over various traffic scenarios generated from a traffic simulator.

Cameras and image processing hardware are rapidly evolving technologies, which enable real-time applications for passenger cars, ground robots, and aerial vehicles. Visual odometry (VO) algorithms estimate vehicle position and orientation changes from the moving camera images. For ground vehicles, such as cars, indoor robots, and planetary rovers, VO can augment movement estimation from rotary wheel encoders. Feature-based VO relies on detecting feature points, such as corners or edges, in image frames as the vehicle moves. These points are tracked over frames and, as a group, estimate motion. Not all detected points are tracked since not all are found in the next frame. Even tracked features may not be correct since a feature point may map to an incorrect nearby feature point. This can depend on the driving scenario, which can include driving at high speed or in the rain or snow.

Global surrogate modeling aims to build surrogate model with high accuracy in the whole design domain. A major challenge to achieve this objective is how to reduce the number of function evaluations to the original computer simulation model. To date, the most widely used approach for global surrogate modeling is the adaptive surrogate modeling method. It starts with an initial surrogate model, which is then refined adaptively using the mean square error (MSE) or maximizing the minimum distance criteria. It is observed that current methods may not be able to effectively construct a global surrogate model when the underlying black box function is highly nonlinear in only certain regions. A new surrogate modeling method which can allocate more training points in regions with high nonlinearity is needed to overcome this challenge. This article proposes an efficient global surrogate modeling method based on a multi-layer sampling scheme.

Simulation based design and control optimization is widely used to assist the development of highly complex modern downsized turbocharged gasoline direct injection (GDI) engines. In such engines, knock phenomenon is a major constraint that limits performance and fuel economy enhancements. Thus, an accurate knock prediction model is critically important for virtual engine development process. In this paper, an enhanced ignition delay model is proposed for spark ignition (S)I combustion model based on previously developed empirical two-stage ignition delay model using fuel blends [1]. The ignition delay model provides a capability of predicting ignition delay of the end-gas zone for different fuel blends without additional calibration when fuel blending ratio changes. To adapt the ignition delay model to the SI combustion environment, the model is modified to have the sensitivity to the dilution effect by residual gas.

Nowadays, the vehicle design is highly ruled by the increasing customer demands and expectations. In addition to ride comfort and vehicle handling, the Noise, Vibration and Harshness (NVH) behavior of the powertrain is also a critical factor that has a big impact on the customer experience. To evaluate the powertrain NVH characteristics, the NVH error states should be studied. A typical NVH event could be decoupled into 3 parts: source, path, and receiver. Take-off shudder, which evaluates the NVH severity level during vehicle take-off, is one of the most important NVH error states. The main sources of Front Wheel Drive (FWD) take-off shudder are the plunging Constant Velocity Joints (CVJ) on the left and right half shafts. This is because a plunging CVJ generates a third order plunging force with half shaft Revolution Per Minute (RPM), which is along the slip of the plunging CVJ.

To reliably implement driver-assist features and ultimately self-driving cars, autonomous driving systems will likely rely on a variety of sensor types including GPS, RADAR, LASER range finders, and cameras. Cameras are an essential sensory component because they lend themselves to the task of identifying object types that a self-driving vehicle is likely to encounter such as pedestrians, cyclists, animals, other cars, or objects on the road. In this paper, we present a feature-based visual odometry algorithm based on a stereo-camera to perform localization relative to the surrounding environment for purposes of navigation and hazard avoidance. Using a stereo-camera enhances the accuracy with respect to monocular visual odometry. The algorithm relies on tracking a local map consisting of sparse 3D map points. By tracking this map across frames, the algorithm makes use of the full history of detected features which reduces the drift in the estimated motion trajectory.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

Determination of an engine's inertial properties is critical during vehicle dynamic analysis and the early stages of engine mounting system design. Traditionally, the inertia tensor can be determined by torsional pendulum method with a reasonable precision, while the center of gravity can be determined by placing it in a stable position on three scales with less accuracy. Other common experimental approaches include the use of frequency response functions. The difficulty of this method is to align the directions of the transducers mounted on various positions on the engine. In this paper, an experimental method to estimate an engine's inertia tensor and center of gravity is presented. The method utilizes the traditional torsional pendulum method, but with additional measurement data. With this method, the inertia tensor and center of gravity are estimated in a least squares sense.

Low frequency torsional vibrations can be a significant source of objectionable vehicle vibrations and in-vehicle boom, especially with changes in engine operation required for improved fuel economy. These changes include lower torque converter lock-up speeds and cylinder deactivation. This paper has two objectives: 1) Examine the effect of increased torsional vibrations on vehicle NVH performance and ways to improve this performance early in the program using test and simulation techniques. The important design parameters affecting vehicle NVH performance will be identified, and the trade-offs required to produce an optimized design will be examined. Also, the relationship between torsional vibrations and mount excursions, will be examined. 2) Investigate the ability of simulation techniques to predict and improve torsional vibration NVH performance. Evaluate the accuracy of the analytical models by comparison to test results.

NVH targets for future vehicles are often defined by utilizing a competitive benchmarking vehicle in conjunction with an existing production and/or reference vehicle. Mode management of full vehicle modes is one of the most effective and significant NVH strategies to achieve such targets. NVH dynamic characteristics of a full vehicle can be assessed and quantified through experimental modal testing for determination of global body mode resonance frequency, damping property, and mode shape. Major body modes identified from full vehicle modal testing are primarily dominated by the vehicle's body-in-white structure. Therefore, an estimate of BIW modes from full vehicle modes becomes essential, when only full vehicle modes from experimental modal testing exist. Establishing BIW targets for future vehicles confines the fundamental NVH behavior of the full vehicle.

This paper describes the application of the modal compliance method to a complex structure such as a vehicle body in white, and the extension of the method from normal modes to the complex modes of a complete vehicle. In addition to the usual bending and torsion calculations, the paper also describes the application of the method to less usual tests such as second torsion, match-boxing and breathing. We also show how the method can be used to investigate the distribution of compliance throughout the structure.

Postal delivery vehicles provide an excellent opportunity for using electric propulsion, since the number of miles driven daily on the delivery route is established and consistent. The vehicles also return nightly to a central depot so charging infrastructure is not an issue as long as the vehicles have sufficient charge to complete the routes. The United States Postal Service has evaluated electric vehicles for postal carrier route vehicles several times. The latest trial concluded in 2001. During the test of electric postal carrier route vehicles, the range was usually adequate for the delivery route; however there were a few instances of vehicles having to be retrieved because they had exhausted their batteries. This paper describes a series hybrid electric vehicle that addresses range issues with an on-board internal combustion engine powered generator to extend vehicle range.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

The need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

Tailor welded steel blanks have long been applied in stamping of automotive parts such as door inner, b-pillar, rail, sill inner and liftgate inner, etc. However, there are few known tailor welded aluminum blanks in production. Traditional laser welding equipment simply does not have the capability to weld aluminum since aluminum has much higher reflectivity than steel. Welding quality is another issue since aluminum is highly susceptible to pin holes and undercut which leads to deterioration in formability. In addition, high amount of springback for aluminum panels can result in dimension control problem during assembly. A tailor-welded aluminum blank can help reducing dimension variability by reducing the need for assembly. In this paper, application of friction stir and plasma arc welded blanks on a liftgate inner will be discussed.

In automotive testing, a chassis dynamometer is typically used, during cell testing, to evaluate vehicle performance by simulating actual driving conditions. The use of indoor cell testing has the advantage of running controlled tests where the cell temperature and humidity and solar loads can be well controlled. Driving conditions such as vehicle speed, wind speed and grade can be also controlled. Thus, repeated tests can be conducted with minimum test variations. The tractive effort required at the wheels of a vehicle for a given set of operating parameters is determined by taking into account a set of variables which affect vehicle performance. The forces considered in determination of the tractive effort include the constant friction force, variable friction force due to mechanical and tire friction, forces due to inertia and forces due to aerodynamic and wind effects. In addition, forces due to gravity are considered when road grades are simulated.

This paper identifies the difference in powertrain cooling system content levels using a nominal and a +3 Standard deviation maximum temperature design approach. Variation simulation analysis tools are used along with a 1-D cooling system performance model to predict resulting temperature distribution for different combinations of input variable populations. The analysis will show differential in powertrain cooling system content, mass, and impact to fuel economy for a nominal vs. +3 sigma design approach.

One Dimensional models for front end air flows through the cooling system package are very useful for evaluating the effects of component and front end geometry changes. To solve such models for the air flow requires a robust iterative process that involves a number of non-linear sub-models. The cooling fan (s) constitute a major part of the difficulty, especially when they employ a viscous or “thermal” fan drive. This drive varies the torque coupling between the input and output shafts based on the radiator outlet air temperature. The coupling is achieved by viscous shear between two grooved disks and is regulated by a bimetal strip valve that varies the amount of fluid between the disks. This paper presents a mathematical model by which the input/output speed ratio may be determined as a function of the air temperature and input speed. Coefficients in the model are estimated from standard supplier performance information.