Search Results

In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

This paper presents the most recent advancement in the vehicle development process using the one-step or auto Transfer Path Analysis (TPA) in conjunction with the superelement, component mode synthesis, and automated multi-level substructuring techniques. The goal is to identify the possible ways of energy transfer from the various sources of excitation through numerous interfaces to given target locations. The full vehicle model, consists of superelements, has been validated with the detailed system model for all loadcases. The forces/loads can be from rotating components, powertrain, transfer case, chain drives, pumps, prop-shaft, differential, tire-wheel unbalance, road input, etc., and the receiver can be at driver/passenger ears, steering column/wheel, seats, etc. The traditional TPA involves two solver runs, and can be fairly complex to setup in order to ensure that the results from the two runs are consistent with subcases properly labeled as input to the TPA utility.

This investigation utilizes a DFSS analysis approach to determine automatic transmission gear content required to minimize fuel consumption for various powertrain - vehicle systems. L18 and L27 inner arrays with automatic transmission design and shift pattern constraint parameters were varied to determine their relative influence on fuel consumption. An outer noise array consisting of two vehicles with various engines, final drive ratios and legislated emissions test cycles was used to make a robust transmission selection based on minimizing fuel consumption. The full details of the DFSS analysis method and assumptions are presented along with a detailed examination of the results. With respect to transmission design parameters, parasitic spinloss and gear mesh efficiency were found to be most important followed by the number of gears. The DFSS analysis further revealed that unique transmission design formulations are potentially required for widely varying engines.

The General Motors (GM) 1ET35 drive unit is designed for an optimum combination of efficiency, performance, reliability, and cost as part of the propulsion system for the 2014 Chevrolet Spark Electric Vehicle (EV) [1]. The 1ET35 drive unit is a coaxial transaxle arrangement which includes a permanent-magnet (PM) electric motor and a low loss single-planetary transmission and is the sole source of propulsion for the battery-only electric vehicle (BEV) Spark. The 1ET35 is designed with experience gained from the first modern production BEV, the 1996 GM EV1. This paper describes the design optimization and development of the 1ET35 and its electric motor that will be made in the United States by GM. The high torque density electric motor design is based on high-energy permanent magnets that were originally developed by GM in connection with the EV1 and GM bar-wound stator technology introduced in the 2Mode Hybrid electric transmission, used in the Chevrolet Volt and in GM eAssist systems.

In the vehicle development process, one important step is to set a component performance target from the vehicle level performance. Conventional barrier-decoupler dash mats and floor trim underlayment systems typically provide sound transmission loss (STL) with minimal absorption. Thus the performance of such components can be relatively easily specified as either STL or Insertion Loss. Lightweight dissipative or multi-layered acoustic materials provide both STL and significant absorption. The net performance is a combination of two parameters instead of one. The target for such components needs to account for this combined effect, however different suppliers use unique formulations and manufacturing methods, so it is difficult and time consuming to judge one formulation against another. In this paper, a unique process is presented to set a component target as a combined effect of STL and absorption.

Response Surface Models are often used as a surrogate for expensive black-box functions during optimization to reduce computational cost. Often, the CAE analysis models are highly nonlinear and multi-modal. A response surface approximation of such analysis as a result is highly multi-modal; i.e. it contains multiple local optima. A gradient-based optimizer working with such a response surface will often converge to the nearest local optimum. There does not exist any method to guarantee a global optima for non-convex multi-modal functions. For such problems, we propose an efficient algorithm to find as many distinct local optima as possible. The proposed method is specifically designed to work in large dimensions (about 100 ∼ 1000 design variables and similar number of constraints) and can identify most of the locally optimal solutions in a reasonable amount of time.

This investigation utilizes energy analysis and statistical methods to optimize step gear automatic transmissions gear selection for fuel consumption. A full factorial matrix of simulations using energy analysis was performed to determine the optimal number of gears and gear ratios that provide the best fuel consumption performance for a particular vehicle - engine application. The full factorial matrix setup as a design of experiment (DOE) was applied to five vehicle applications, each with two engines to examine the potential differences that variations in road load and engine characteristics might have on optimal transmission gearing selection. The transmission gearing options considered in the DOE were number of gears, launch gear ratio and top gear ratio. Final drive ratio was also included due to its global influence on vehicle performance and powertrain operating speeds and torque.

Spot weld separation in vehicle development stage is one of the critical phenomena in structural analyses regarding quasi-static test condition, like roof strength or seat/belt pull. It directly reduces structural performance by losing connected load path and occasionally introduces tearing on surrounding sheet metals. Traditionally many efforts have been attempted to capture parent metal ductile fracture, but not applied to spot weld separations in automotive FEA simulations. [1,2,3] This paper introduces how to develop FFLD failure criteria from a series of parametric study on ultra high strength sheet steel and deals with failure criteria around spot weld and parent metal. Once the fracture strains for sheet steels are determined, those developed values were applied to traditional spot weld coupon FEA simulations and tests. Full vehicle level roof strength FEA simulations on a typical automotive body structure were performed and verified to the physical tests.

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.

This paper will examine the various design and performance criteria for optimized internal heat exchanger performance as applied to R134a and HFO-1234yf systems. Factors that will be considered include pressure drop, heat transfer, length, internal surface area, the effect of oil in circulation, and how these factors impact the effectiveness of the heat exchanger. The paper describes the test facility used and test procedures applied. Furthermore, some design parameters for the internal heat exchanger will be recommended for application to each refrigerant.

A new solution methodology for optimal spot-weld pattern design is presented. The objective of the optimization is to minimize the total number of welds in a structure while maintaining structural properties above a required level. Two approaches were developed, based on the representation of welds in a finite element model. In the approach ‘without ranking’ welds are represented in a traditional way, as rigid connections. In ‘with ranking’ approach welds are treated as elastic elements subjected to stresses and deformations under given loading conditions. The information on weld stress is utilized in the solution process to reduce the number of design variables and improve the quality of the solution. The applicability of the method to large automotive structures was demonstrated, as well as the capacity for optimization with respect to multiple load sets.

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 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.

This work analyzes the lubricant supply to critical regions of needle roller bearing of an automatic transmission. The needle roller bearing is a critical component of an automatic transmission and it has several rotating cylindrical needle rollers that are having relative motion with inner surface of the pinion. Supply of lubricant to the needle roller bearings is very essential to prevent failure of the bearings due to frictional contact between rollers and inner surface of pinion. The supply of lubricant to the needle roller bearings depends on the location of oil supply hole. Lubricant supply to the needle roller bearings of an automatic transmission is studied using commercial 3D Computational Fluid Dynamics (CFD) software for different oil supply positions. CFD simulation is performed for the region between the pinion supply hole and end of the needle bearings including all needles. Lubricant is supplied to the needle bearing from the pinion pin oil supply hole.

Oil canning and initial stiffness of the automotive roofs and panels are considered to be sensitive customer ‘perceived quality’ issues. In an effort to develop more accurate objective requirements, respective simulation methods are continuously being developed throughout automotive industries. This paper discusses a latest development on oil canning predictions using LS-DYNA® Implicit, including BNDOUT request, MORTAR contact option and with the stamping process involved, which resulted in excellent correlations especially when it comes to measurements at immediate locations to the feature lines of the vehicle outer panels. Furthermore, in pursuit of light-weighting vehicles with thinner roofs, a new CAE method was recently developed to simulate severe noise conditions exhibited on some of developmental properties while going through a car wash.

AUTOSAR(AUTomotive Open System ARchitecture) establishes an industry standard for OEMs and the supply chain to manage growing complexity to the automotive electronics domain. Increased focus on software based features will prove to be a key differentiator between vehicle platforms. AUTOSAR serves to standardize automotive serial data communication protocols, interaction with respect to hardware peripherals within an ECU and allow ECU implementer to focus on development of unique customer focused features that distinguish product offerings. Adoption strategy and impact assessment associated with leveraging AUTOSAR for an E/E Architecture and the potential challenges that need to be considered will be described in this publication. This publication will also illustrate development strategies that need to be considered w.r.t deploying AUTOSAR like data exchange, consistency to BSW software implementation, MCAL drivers etc.

The ASTM Sequence IIID engine-dynamometer test has been used to evaluate the high-temperature protection provided by engine oils with respect to valve train wear, viscosity increase (oil thickening), deposits, and oil consumption. The obsolescence of the engine used in this test along with the need to define even higher levels of performance associated with a new oil category (SG) prompted efforts at developing a replacement test. This paper describes the hardware and procedure development of this replacement test, the ASTM Sequence IIIE test. Test precision and correlation with field and Sequence IIID results on a series of reference oils is also discussed.

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.

This paper presents the Component Dynamic Synthesis (CDS) superelement creation, which contains the loading frequency information and is much faster than the Component Mode Synthesis (CMS) method in the residual run. The Frequency Response Functions (FRFs) are computed using the direct frequency response method and the inversion of dynamic stiffness matrix is done using the singular value decomposition (SVD) method for every discrete frequency in the frequency range of interest. The CDS will be very efficient and economical for design of experiments and robust optimization, where hundreds of runs are required. The CDS super element can be used when there is a large number of residual runs on a very large vehicle model at higher end of the frequency range of study. For the residual analysis to run as fast as possible, all components, except very small ones, need to be converted into CDS superelements.