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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.

General Motors shall introduce a new rear wheel drive eight speed automatic transmission, known as the 8L90, in the 2015 Chevrolet Corvette. The rated turbine torque capacity is 1000 Nm. This transmission replaces the venerable 6L80 six speed automatic. The objectives behind creation of this transmission are improved fuel economy, performance, and NVH. Packaging in the existing vehicle architecture and high mileage dependability are the givens. The architecture is required to offer low cost for a rear drive eight speed transmission while meeting the givens and objectives. An eight speed powerflow, invented by General Motors, was selected. This powerflow yields a 7.0 overall ratio spread, enabling improved launch capability because of a deeper first gear ratio and better fuel economy due to lower top gear N/V capability, relative to the 6L80. The eight speed ratios are generated using four simple planetary gearsets, two brake clutches, and three rotating clutches.

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.

Laser welding of dissimilar metals such as Aluminum and Copper, which is required for Li-ion battery joining, is challenging due to the inevitable formation of the brittle and high electrical-resistant intermetallic compounds. Recent research has shown that by using a novel technology, called laser braze-welding, the Al-Cu intermetallics can be minimized to achieve superior mechanical and electrical joint performance. This paper investigates the robustness of the laser braze-welding process. Three product and process categories, i.e. choice of materials, joint configurations, and process conditions, are studied. It is found that in-process effects such as sample cleanness and shielding gas fluctuations have a minor influence on the process robustness. Furthermore, many pre-process effects, e.g. design changes such as multiple layers or anodized base material can be successfully welded by process adaption.

The energy storage system (ESS) is the key enabler to hybrid electric vehicles (HEVs) that offer improved fuel economy and reduced vehicle emissions. The power capability of a battery has significant impact on the fuel economy of HEVs. This paper presents the power capability testing of a lithium-ion battery with a conventional metal oxide cathode using the hardware in the loop (HIL) at a wide range of charge/discharge conditions and at different temperatures. The achieved test results provide critical data of battery power characteristics and effectively accelerate the development of battery power prediction algorithm.

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.

More and more advanced features such as adaptive cruise control and collision avoidance are being adopted in road vehicles and these features are usually implemented as distributed systems across multiple ECU nodes that are connected by communication busses. In order to tolerate transient faults affecting a safety critical signal transmitted via bus in such distributed systems, the last used value or a default safe value for a safety critical signal is usually used among different ECU nodes on the bus for a pre-defined time interval before taking some other fault mitigation actions such as disabling a feature. Thus it becomes very important to monitor a signal's age and detect any signal age fault, where a signal age fault is defined as the use of an older or default signal value for longer than or equal to the pre-defined time interval.

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 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.

This paper describes the capabilities of a new two-motor plug-in hybrid-electric propulsion system developed for rear wheel drive. The PHEV system comprises a 2.0L turbocharged 4-cylinder direct-injected gasoline engine with the new hybrid transmission [1], a new traction power inverter module, a liquid-cooled lithium-ion battery pack, and on-board battery charger and 12V power converter module. The capability and features of the system components are described, and component performance and vehicle data are reported. The resulting propulsion system provides an excellent combination of electric-only driving, acceleration, and fuel economy.