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Current generation automobiles are controlled by electronic modules for performing various functions. These electronic modules have numerous semiconductor devices mounted on printed circuit boards. Solders are generally used as thermal interface material between surface mount devices and printed circuit boards (PCB) for efficient heat transfer. In the manufacturing stage, voids are formed in solders during reflow process due to outgassing phenomenon. The presence of these voids in solder for power packages with exposed pads impedes heat flow and can increase the device temperature. Therefore it is imperative to understand the effect of solder voids on thermal characteristics of semiconductor devices. But the solder void pattern will vary drastically during mass manufacturing. Replicating the exact solder void pattern and doing detail simulation to predict the device temperature for each manufactured module is not practical.

Wire shorts on an in-vehicle controller area network (CAN) impact the communication between electrical control units (ECUs), and negatively affects the vehicle control. The fault, especially the intermittent fault, is difficult to locate. In this paper, an equivalent circuit model for in-vehicle CAN bus is developed under the wire short fault scenario. The bus resistance is estimated and a resistance-distance mapping approach is proposed to locate the fault. The proposed approach is implemented in an Arduino-based embedded system and validated on a vehicle frame. The experimental results are promising. The approach presented in this paper may reduce trouble shooting time for CAN wire short faults and may enable early detection before the customer is inconvenienced.

Aerodynamic vehicle design improvements require flow simulation driven iterative shape changes. The 3-D flow field simulations (CFD analysis) are not explicitly descriptive in providing the direction for aerodynamic shape changes (reducing drag force or increasing the down-force). In recent times, aerodynamic shape optimization using the adjoint method has been gaining more attention in the automotive industry. The traditional DOE (Design of Experiment) optimization method based on the shape parameters requires a large number of CFD flow simulations for obtaining design sensitivities of these shape parameters. The large number of CFD flow simulations can be significantly reduced if the adjoint method is applied. The main purpose of the present study is to demonstrate and validate the adjoint method for vehicle aerodynamic shape improvements.

Development of the next generation internal combustion engines and automatic transmissions for automotive applications is a mandatory powertrain engineering activity required now and in the coming years to meet forthcoming global emissions regulations. This paper details a preliminary investigation into possible synergies for fuel consumption reduction considering emerging automotive technologies integrated into the next generation combustion engine and automatic transmission architectures. A range of hypothetical gasoline engines were created and paired with a generalized set of step gear automatic transmissions designed to meet the performance requirements of high volume longitudinal full size truck application. These designs were then run through a design of experiments orthogonal array for prediction of fuel consumption on the WLTP test schedule and stand still acceleration to 100 kph.

New seal cross-section development is a very tedious and time consuming process if conventional analysis methods are used, as it is very difficult to predict the dimensions of the seal that will satisfy the sealing performance targets. In this study, a generic cross-section is defined and the design constraints are specified. Isight then runs the FEA model, utilizing a custom python script for post-processing. Isight then updates the dimensions of the seal and continues running analyses. Isight was run using two different design exploration techniques. The first was a design of experiments (DOE) to discover how the seal’s response varies with its dimensions. Then, after the analyst examined the results, Isight was run in optimization mode focusing on feasible design areas as determined from the DOE. Thus, after the initial model setup, the user can run the analyses in the background and only needs to interact with the program after Isight has determined a list of feasible designs.

The quality of material model input files for finite element analysis (FEA) is a fundamental factor governing the fidelity and accuracy of simulations at a sub-system or a vehicle level, dictating an investment of due diligence in developing and validating the material models. Several material models conventionally employed for FEA typically allow accounting for only uniaxial tensile behavior of the material; however, the models may be required to predict component-level response in a complex loading scenario. Therefore in developing LSDYNA material input files for such models, it becomes critical to validate their performance in alternative loading scenarios. For out-ofplane loading, typically a three or four-point bending load-case is used for validation. Simulating three point bending (TPB), particularly in the quasi-static regime, requires detailed representation of the moving pin impacting the specimen, and sliding of the specimen on the stationary pins.

The electric vehicle on-board charger (OBC) is responsible for converting AC grid energy to DC energy to charge the battery pack. This paper describes the development of GM’s second generation OBC used in the 2016 Chevrolet Volt. The second generation OBC provides significant improvements in efficiency, size, and mass compared to the first generation. Reduced component count supports goals of improved reliability and lower cost. Complexity reduction of the hardware and diagnostic software was undertaken to eliminate potential failures.

The Cadillac CT6 plug-in hybrid electric vehicle (PHEV) power-split transmission architecture utilizes two motors. One is an induction motor type while the other is a permanent magnet AC (PMAC) motor type referred to as motor A and motor B respectively. Bar-wound stator construction is utilized for both motors. Induction motor-A winding is connected in delta and PMAC motor-B winding is connected in wye. Overall, the choice of induction for motor A and permanent magnet for motor B is well supported by the choice of hybrid system architecture and the relative usage profiles of the machines. This selection criteria along with the design optimization of electric motors, their electrical and thermal performances, as well as the noise, vibration, and harshness (NVH) performance are discussed in detail. It is absolutely crucial that high performance electric machines are coupled with high performance control algorithms to enable maximum system efficiency and performance.

The Computer-Aided Engineering of Automotive Batteries (CAEBAT) Phase 1 project is a U.S. Department of Energy-funded, multi-year project which is aimed at developing a complete CAE tool set for the automotive battery pack design. This paper reports the application of the full field approach of the CAEBAT which is developed by the General Motors-led industry team, for a 24-cell liquid-cooled prototype battery pack. It also summarizes the verification of the approach by comparing the simulation results with the measurement data. The simulation results using the Full Field Approach are found to have a very good agreement with the measurement data.

Delphi is developing a new combustion technology called Gasoline Direct-injection Compression Ignition (GDCI), which has shown promise for substantially improving fuel economy. This new technology is able to reuse some of the controls common to traditional spark ignition (SI) engines; however, it also requires several new sensors and actuators, some of which are not common to traditional SI engines. Since this is new technology development, the required hardware set has continued to evolve over the course of the project. In order to support this development work, a highly capable and flexible electronic control system is necessary. Integrating all of the necessary functions into a single controller, or two, would require significant up-front controller hardware development, and would limit the adaptability of the electronic controls to the evolving requirements for GDCI.

Mahalanobis Distance (MD) is gaining momentum in many fields where classification, statistical pattern recognition, and forecasting are primary focus. It is a multivariate method and considers correlation relationships among parameters for computing generalized distance measure to separate groups or populations. MD is a useful statistic in multivariate analysis to test that an observed random sample is from a multivariate normal distribution. This capability alone enables engineers to determine if an observed sample is an outlier (defect) that falls outside the constructed (good) multivariate normal distribution. In Mahalanobis-Taguchi System (MTS), MD is suitably scaled and used as a measure of severity in abnormality assessment. It is obvious that computed MD depends on values of parameters observed on a random sample. All parameters may not equally impact MD. MD could be highly sensitive with respect to some parameters and less sensitive to some other parameters.

Several application developers are currently faced with the problem of moving a complex system from a single-core to a multicore platform. The problem encompasses several issues that go from modeling issues (the need to represent the system features of interest with sufficient accuracy) to analysis and optimization techniques, to the selection of the right formulations for constraints that relate to time. We report on the initial findings in a case study in which the application of interest is a fuel injection system. We provide an analysis on the limitations of AUTOSAR and the existing modeling tools with respect to the representation of the parameters of interest for timing analysis, and we discuss applicable optimization methods and analysis algorithms.

Development of the software using fixed-point arithmetic is known to be tedious and error-prone. Difficulty of selecting the correct data type can outwear software developers. The common retreats often sought after include manual calculation of the approximate ranges, exhaustive simulations with extreme input values and conservative development approach by using excessive word length. The first two retreats - manual calculation and exhaustive simulations - increase the software development time, and the third retreat - conservative development - leads to the excessive memory (RAM and ROM) utilization by the software. The model-based development environment such as the Simulink has graphical nature to the software with flow of data defined by connecting signal lines. The model-based software therefore gives an opportunity to trace signal flow in the software. Input-tracing method is presented to trace the flow of the input signals of the user selected block in the software model.

A GT-Power Fast Run Model simplified from detail model for HIL is verified with a bench test using the dSPACE Simulator. Firstly, the conversion process from a detailed model to FRM model is briefly described. Then, the spark timing, fuel pulse with control for FAR, and torque level control are developed for proof of concept. Moreover a series of FRM/Simulink co-simulation and HIL tests are conducted. In the summary, the test results are presented and compared with GT detailed model simulations. The test results show that the FRM/dSPACE HIL stays consistent in most variables of interest under 0.7-0.9 real-time factor condition between 1000 - 5000 RPM. The same steady-state can be reached by RCP controllers or with GT-Power internal controllers. The transient states are close using different control algorithm. The main purpose of HIL application is achieved, despite inconsistencies in performance data like fuel consumption.

A permanent magnet synchronous motor (PMSM) motor is used to design the propulsion system of GM’s Chevrolet Bolt battery electric vehicle (BEV). Magnets are buried inside the rotor in two layer ‘V’ arrangement. The Chevrolet Bolt BEV electric machine rotor design optimizes the magnet placement between the adjacent poles asymmetrically to lower torque ripple and radial force. Similar to Chevrolet Spark BEV electric motor, a pair of small slots are stamped in each rotor pole near the rotor outer surface to lower torque ripple and radial force. Rotor design optimizes the placement of these slots at different locations in adjacent poles providing further reduction in torque ripple and radial force. As a result of all these design features, the Chevrolet Bolt BEV electric motor is able to meet the GM stringent noise and vibration requirements without implementing rotor skew, which (rotor skew) lowers motor performance and adds complexity to the rotor manufacturing and hence is undesirable.

The ever-increasing regulatory requirement on CO2 emissions drives efficiency improvement of vehicle powertrain systems. In this context, three mega trends have been happening in the automotive transmission industry. First, future automatic transmissions will have more gear steps to offer a broader ratio spread and finer ratio steps, which may enable the engine to operate at its efficient regions more often. Second, engine downsizing with boosted power and flexible cylinder deactivation have been become the technology trend to achieve better thermal efficiency. These engine technologies demand improved transmission dampers with greater isolation capabilities to drive future transmission dampers to be equipped with softer springs. Third, future transmissions will be more efficient due to new architectures and incremental subsystem improvements.

GM has developed an all-new gasoline-electric hybrid powertrain for the model year 2016 Chevrolet Malibu Hybrid vehicle, which was designed to achieve excellent fuel economy, performance, and drive quality. The powertrain shares the transmission architecture with the 2016 Chevrolet Volt extended range electric vehicle, but includes changes to optimize the system for engine driven charge sustaining operation in the range of conditions represented by the US EPA 5 cycle fuel economy tests. In this paper, we describe the Malibu Hybrid propulsion system features and components, including the battery pack, transaxle, electric motors and power electronics, engine, and thermal system. The modifications between the Volt and Malibu Hybrid propulsion systems are discussed and explained as resulting from the differences between the primarily electric and gasoline powered applications.

Building on the experience of the Chevrolet Spark EV battery electric vehicle, General Motors (GM) has developed a propulsion system with increased capability for its next generation Chevrolet Bolt EV. It propels a new larger electric vehicle with significantly greater electric driving range. Through extensive analysis the primary propulsion system components, which include the drive unit, traction electric motor, power electronics, energy storage, and on-board charging module, were optimized individually and as an integrated system to deliver improvements in propulsion system energy, power, torque and efficiency. The results deliver outstanding EV range and fun-to-drive acceleration performance.

Wind tunnel testing of reduced-scale models is a valuable tool for aerodynamic development during the early stages of a new vehicle program, when basic design themes are being evaluated. Both full-and reduced-scale testing have been conducted for many years at the General Motors Aerodynamics Laboratory (GMAL), but with increased emphasis on aerodynamic drag reduction, it was necessary to identify additional facilities to provide increased test capacity. With vehicle development distributed among engineering teams around the world, it was also necessary to identify facilities local to those teams, to support their work. This paper describes a cooperative effort to determine the correlation among five wind tunnels: GMAL, the Glenn L.

Sound absorption materials can be key elements for mass-efficient vehicle noise control. They are utilized at multiple locations in the interior and one of the most important areas is the roof. At this location, the acoustic treatment typically comprises a headliner and an air gap up to the body sheet metal. The acoustic performance requirement for such a vehicle subsystem is normally a sound absorption curve. Based on headliner geometry and construction, the sound absorption curve shape can be adjusted to increase absorption in certain frequency ranges. In this paper an overall acoustic metric is developed to relate design parameters to an absorption curve shape which results in improved in-vehicle performance. This metric is based on sound absorption coefficient and articulation index. Johnson-Champoux-Allard equivalent fluid model and diffuse field equations are used. The results are validated using impedance tube measurements.