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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.

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.

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.

Finite element dummy models have been more and more widely applied in virtual development of occupant protection systems across the automotive industry due to their predictive capabilities. H350 dyna dummy model [1] is a finite element representation of the Hybrid III male dummy [2], which is designed to represent the average of the United States adult male population. Lower extremity injuries continue to occur in front crash accidents despite increasing improvement of vehicle crashworthiness and occupant restraint system. It is therefore desirable to predict lower tibia injury numbers in front occupant simulations. Though lower tibia loading/index predictions are not studied as much as the FMVSS 208 regulated injury numbers, the tibia indices are injury criteria that need to be assessed during IIHS and Euro NCAP frontal offset occupant simulations. However during front crash simulations, it is very difficult to achieve good correlations or predictions of lower tibia loadings.

It is obvious at this point even to the most casual observer of the automotive industry that efforts to reduce mass throughout the vehicle are at a fervor. The industry is facing its most significant increase in fuel economy standards in its history, and light-weighting the vehicle is a major enabler. Despite the performance and quality of the brake system being intensely related to its mass, it too has not been spared scrutiny. However, like many modern automotive subsystems, it is very complex and mass reduction opportunities that do not sacrifice performance or quality are not always obvious. There are some interesting and sometimes even profound relationships between mass and other vehicle attributes built into brake system design, and making these more visible can enable a better balancing of brake system with the rest of the vehicle design objectives. Examples include - what is the cost, in terms of brake system mass, of added engine power? Of tire and wheel size?

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.

A new approach for modeling and analysis of a transmission and driveline system is proposed. By considering the stiffness, damping and inertias, model equations based on lumped parameters can be created through standard Lagrangian Mechanics techniques. A sensitivity analysis method has then been proposed on the eigenspace of the system characteristic equation to reveal the dynamic nature of a transmission and driveline system. The relative sensitivity calculated can clearly show the vibration modes of the system and the key contributing components. The usefulness of the method is demonstrated through the GM 6-speed RWD transmission by analyzing the dynamic nature of the driveline system. The results can provide a fundamental explanation of the vibration issue experienced and the solution adopted for the transmission.

General Motors has introduced a new front wheel drive seven speed dry dual clutch automatic transmission in 2014. The 250 Nm input torque rated gear box was designed and engineered for a global market in both front wheel drive and all-wheel drive configurations. The transmission has integrated start/stop capability enabled by the use of an electric motor driven pump and a pressurized accumulator. The architecture selected was chosen for optimization of packaging, fuel economy, mass, shift pleasability, and NVH. High mileage durability and world class drivability were the cornerstone deliverables during the engineering and design process Fuel efficiency is estimated to be 3% - 10% improvement over a conventional six speed automatic transmission. FWD variant wet mass of 78.1 kg was achieved through the rigorous engineering processes used to optimize the transmission system.

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.

With the ever increasing pressure to improve the fuel economy of vehicles, there has been a corresponding interest in reducing the mass and size of vehicles. While mass is easily quantifiable, vehicle size, particularly the notion of “interior space” as perceived by the customer, is not. This paper explores different ways in which vehicle spaciousness can be quantified and explores new metrics based on customer verbatims. A novel ‘spaciousness calculator’ combines individual metrics to provide a singular holistic rating for spaciousness, useful during vehicle development. Beyond spaciousness, the paper discusses techniques to quantify the ‘packaging efficiency’ of a vehicle; this allows engineers to maximize the interior space for a given exterior size.

An area of brake system design that has remained continually resistant to objective, computer model based predictive design and has instead continued to rely on empirical methods and prior history, is that of sizing the brake pads to insure satisfactory service life of the friction material. Despite advances in CAE tools and methods, the ever-intensifying pressures of shortened vehicle development cycles, and the loss of prototype vehicle properties, there is still considerable effort devoted to vehicle-level testing on public roads using “customer-based” driving cycles to validate brake pad service life. Furthermore, there does not appear to be a firm, objective means of designing the required pad volume into the calipers early on - there is still much reliance on prior experience.

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.

In a math-based control algorithm design, model-based simulation and testing are very important as an integral part of design process. There are many advantages of using modeling and simulation in the algorithm design. In this paper, Algorithm-in-the-Loop and Hardware-in-the-Loop approaches are adopted for a transmission control algorithm development. A practical approach is introduced on how to test the control algorithms with a reliable plant (virtual engine, transmission, and vehicle) model in the closed-loop simulation. In using combination of open-loop and closed-loop simulations, various key behavior test cases are developed and documented for the success of control algorithms development. Secondly, the same test cases are reused and verified against the production codes, which are automatically generated from the math-based control algorithm models.

Surface distortions are frequently introduced into the Class “A” surfaces during various sheet metal forming operations such as drawing, trimming and flanging. The origins of those surface distortions have not been well understood. The scope of this research is to investigate the distortion that occurs in draw operation and to find effective and practical corrective methods. Five geometric parameters are first identified to represent a typical depression feature in automobile outer panels. Experimental dies are then designed to reflect various combinations of these five geometric parameters with the assistance of numerical simulations to ensure that the dies can make parts free of major defects like splits and wrinkles. Surface distortions are observed in our stamping experiments and various techniques are used to measure and record the distortions for further mathematical analysis.

“Wheel balancing” is one of the common automotive repairs that the owners of an automobile usually experience. An unbalanced set of a tire and a rim or wheel on which the tire is mounted could cause vibration while driving. Such vibrations may be sensed by the driver at the steering wheel (known as smooth road shake). If left untreated for a long period of time, the vibration, induced by the imbalance, may propagate to chassis components such as bearing and bushing. This in turn causes excessive wear that eventually leads to a premature failure. Therefore, an early detection of wheel imbalances can not only significantly reduce the cost and time for diagnosis and repair of the wheel, but also prevent further damage to chassis components. This paper studies the feasibility of real-time detection of wheel imbalances in real world driving conditions, using recursive least square estimation method. The simulation study shows promising results for implementation in a real vehicle.

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 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.