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Efficient thermal management is essential in high power density electric drive units (EDUs) due to limited space and working environment. Major heat sources in EDUs are from the inverter, motor and gearbox. System level thermal response prediction models comprising various components within the EDU are of interest from both product performance and software controls standpoint. A system level physics-based lumped parameter thermal network (LPTN) model is built in a one-dimensional (1D) framework using inputs from empirical, electromagnetic, three-dimensional conjugate fluid/heat transfer analysis and test data to predict the component temperature within the EDU. Empirical models were used to calculate heating due to efficiency loss from the gearbox. The thermal loses from the motor are estimated as outputs from electromagnetic simulations.

Electronically locking differentials that have dog-clutches may not always have a smooth engagement. The duration of the engagements needs to be quantified, and the different types of engagement need to be qualified. The engagement time is dictated by both the mechanical and electrical sub-systems of the differential. Three different analytical methods were developed to simulate engagement. The first method uses Simulink to co-simulate the electromagnetic behavior of the actuator in ANSYS Maxwell, and the multibody dynamic behavior of the differential in MSC ADAMS. The second method simulates the mechanics of the differential in AMESim, where an equation for the electromagnetic force inside the actuator is integrated into the model. The third method leverages the former two methods by combining the MSC ADAMS multibody dynamic behavior with integrated equation for the electromagnetic force inside the actuator.

Over the years, requirements for an electric drive for traction applications have increased substantially in terms of efficiency, power density, packaging space and cost. Manufacturers have employed various strategies to achieve high efficiency and power dense solutions. One such strategy is to use a synergistic approach by combining typical EDU sub-components such as an inverter, a motor and a gearbox with a differential to form a fully integrated 3-in-1 solution. Electrical and thermal losses from such a system can be quite significant as it includes losses from the inverter, the motor and the gearbox. As a result, thermal performance is often a limiting factor in improving the packaging space and power density. To address thermal issues, an effective liquid cooling system must be employed that ensures sufficient heat dissipation from all of the EDU subcomponents and helps to reduce packaging space.

Automotive electric drive unit designs are often limited by installation space and the related environmental conditions. Electrical losses in various components of the motor such as stator, rotor and coils can be significant and as a result, the thermal design can become a bottle neck to improve power and torque density. In order to mitigate the thermal issue, an effective liquid cooling system is often employed that ensures sufficient heat dissipation from the motor and helps to reduce packaging size. Although both stator and rotor are cooled in a typical motor, this paper discusses a multiphase oil-air mixture analysis on a spinning hollow rotor and rotor shaft subjected to forced oil cooling. Three-dimensional computational fluid dynamics (CFD) conjugate heat transfer (CHT) simulations were carried out to investigate flow and heat transfer. The effect of centrifugal force, shaft RPM, density gradients and secondary flows were investigated.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

We start our study with a survey of existing variable valve actuation (VVA) devices. We then describe our work, taken place over a time period from 2001 to 2007, on several VVA concepts. All of our projects described include pre-design modeling and simulation. Also, for each one of the proposed designs, a bench-top motorized test fixture was built and ran for proof of concept. Our projects represent a mixture of exploratory research and production-related development work. They can be classified in four broad categories: discrete-step systems; mechanical continuously-variable systems; active stationary-hydraulic lash adjusters; cam-driven hydraulic-lost-motion mechanism. These devices differ in their complexity and versatility but offer a spectrum of design solutions applicable to a range of products. Specific attributes of these different approaches are analyzed and discussed, and some test results are presented.

The Advanced Engineering (AE) group within General Motors Powertrain (GMPT) develops next generation engines and transmissions for automotive and marine products. As a research organization, AE needs to prototype design ideas quickly and inexpensively. To this end, AE has embraced model-based development techniques and is currently investigating the benefits of software in-the-loop (SIL) testing. The underlying obstacle faced in developing a practical SIL system lays in the ability to integrate a plant model with sufficient fidelity together with target application software. ChiasTek worked with AE utilizing their CosiMate tool chain to eliminate these barriers and delivered a flexible SIL system simulation solution.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.

Springback is a major concern in stamping of advanced high strength steels (AHSS). The existing computer simulation technology has difficulty predicting this phenomenon accurately even though it is well developed for formability simulations. Great efforts made in recent years to improve springback predictions have achieved noticeable progress in the computational capability and accuracy. In this work, springback simulation studies are conducted using FEA software LS-DYNA®. Various parametric sensitivity studies are carried out and key variables affecting the springback prediction accuracy are identified. Recently developed simulation technologies in LS-DYNA® are implemented including dynamic effect minimization, smooth tool contact and newly developed nonlinear isotropic/kinematic hardening material models. Case studies on lab-scale and full-scale industrial parts are provided and the predicted springback results are compared to the experimental data.

In racetrack conditions, brake systems are subjected to extreme energy loads and energy load distributions. This can lead to very high friction surface temperatures, especially on the brake corner that operates, for a given track, with the most available traction and the highest energy loading. Individual brake corners can be stressed to the point of extreme fade and lining wear, and the resultant degradation in brake corner performance can affect the performance of the entire brake system, causing significant changes in pedal feel, brake balance, and brake lining life. It is therefore important in high performance brake system design to ensure favorable operating conditions for the selected brake corner components under the full range of conditions that the intended vehicle application will place them under. To address this task in an early design stage, it is helpful to use brake system modeling tools to analyze system performance.

At the early design stage it is easier to achieve impacts on the brake noise. However most noise analyses are applied later in the development stage when the design space is limited and changes are costly. Early noise analysis is seldom applied due to lack of credible inputs for the finite element modeling, the sensitive nature of the noise, and reservations on the noise event screening of the analysis. A high quality brake finite element model of good components’ and system representation is the necessary basis for credible early noise analysis. That usually requires the inputs from existing production hardware. On the other hand in vehicle braking the frequency contents and propensity of many noise cases are sensitive to minor component design modifications, environmental factors and hardware variations in mass production. Screening the noisy modes and their sensitivity levels helps confirm the major noisy event at the early design stage.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

This paper describes the methodology used to design and perform a CFD analysis of a Chevrolet Impala SS Funny Car body. This body was designed for the purpose of making it available for teams to race it in the National Hot Rod Association (NHRA) drag racing series beginning with the 2007 race season. Several challenges were presented in this project: (1) This was the first time a General Motors drag racing body for use in professional classes (Funny Car or otherwise) was ever designed in CAD. (2) The body was originally designed as a 2007 Chevrolet Monte Carlo. After the tooling was completed, changes in Chevrolet’s product lineup required that the body be changed to a 2007 Impala SS. (3) Budget constraints precluded CFD analysis until after the bodies were already being manufactured. There were several teams that raced the new body during the 2007 race season. One of these teams won the Funny Car Driver’s Championship.

The work presented in this paper outlines the development of a simulation model to aid in the design and development of a compliant sprocket for balancer drives. A design with dual-mass flywheel and a crank-mounted compliant chain sprocket greatly reduces interior noise levels due to chain meshing. However, experimental observations showed the compliant sprocket can enter into resonance and generate excessive vibration energy during startup. Special features are incorporated into the compliant sprocket design to absorb and dissipate this energy. Additional damper spring rate, high hysteresis and large motion angle that overlap the driving range may solve the problem during engine start-up period. This work develops a simulation model to help interpret the measured data and rank the effectiveness of the design alternatives. A Multibody dynamics system (MBS) model of the balancer chain drive has been developed, validated, and used to investigate the chain noise.

Sequel is the third vehicle in GM's Reinvention of the Automobile and is the first zero emissions passenger vehicle to drive more than 300 miles on public roads without refueling or recharging. It is purpose-built around the hydrogen storage and fuel cell systems and uses the skateboard principle introduced in the Autonomy vision concept and the Hy-wire proof-of-concept vehicles. Sequel's aluminum structure, Flexray controlled chassis-by-wire systems and AWD system comprising a single front electric motor and two rear wheel motors make it, perhaps, the most technically advanced automobile ever built. The paper describes the vehicle's design and performance characteristics.

Efforts by vehicle manufacturers to reduce road testing have resulted in an increased reliance on the simulation methods for loads measurement and validation, including increased emphasis on methods to characterize and digitally represent test road inputs. Accurate terrain models are especially important in the case of large dynamic road inputs, and for evaluation of vehicle suspension loads and durability. In contrast to direct terrain topology measurement, methods to estimate test road input using only vehicle suspension measurements and a tire dynamic model will be presented. Applications of terrain models for generic simulation and testing will also be discussed.

This paper suggests a scientific approach to designing conservative tests based on computer simulation of the influence of the sources of variations. The idea is to design the conservative test so that, even in the presence of variation, there is a high probability that a random test will have a better result than the conservative test. Therefore, if the conservative test meets the requirement, one has a scientific reason to believe that any random test would have a high probability of meeting it. This new approach is illustrated for FMVSS301 80 kph 70% rear offset deformable barrier impact.

General Motors' 3.6L DOHC 4V V6 engine has been upgraded to provide substantial improvements in performance, fuel economy, and emissions for the 2008 model year Cadillac CTS and STS. The fundamental change was a switch from traditional manifold-port fuel injection (MPFI) to spark ignition direct injection (SIDI). Additional modifications include enhanced cylinder head and intake manifold air flow capacities, optimized camshaft profiles, and increased compression ratio. The SIDI fuel system presented the greatest opportunities for system development and optimization in order to maximize improvements in performance, fuel economy, and emissions. In particular, the injector flow rate, orifice geometry, and spray pattern were selected to provide the optimum balance of high power and torque, low fuel consumption, stable combustion, low smoke emissions, and robust tolerance to injector plugging.