Search Results

The vehicle chassis integrated control system can improve the stability of vehicles under extreme conditions using tire force allocation algorithm, in which, the nonlinearity and uncertainty of tire-road contact condition need to be taken into consideration. Thus, An MPC (Model Predictive Control) controller is designed to obtain the additional steering angle and the additional yaw moment. By using a robust optimal allocation algorithm, the additional yaw moment is allocated to the slip ratios of four wheels. An SMC (Sliding-Mode Control) controller is designed to maintain the desired slip ratio of each wheel. Finally, the control performance is verified in MATLAB-CarSim co-simulation environment with open-loop manoeuvers.

A direct trajectory optimization approach is developed to assess the capability of a GTDI-DCT Powertrain, with a Gasoline Turbocharged Direct Injection (GTDI) engine and Dual Clutch Transmission (DCT), to satisfy stringent drivability requirements during launch. The optimization is performed directly on a high fidelity black box powertrain model for which a single simulation of a launch event takes about 8 minutes. To address this challenging problem, an efficient parameterization of the control trajectory using Gaussian kernel functions and a Mesh Adaptive Direct Search optimizer are exploited. The results and observations are reported for the case of clutch torque optimization for launch at normal conditions, at high altitude conditions and at non-zero grade conditions. The results and observations are also presented for the case of simultaneous optimization of multiple actuator trajectories at normal conditions.

Exhaust Gas Recirculation (EGR) coolers are commonly used in diesel and modern gasoline engines to reduce the re-circulated gas temperature. A common problem with the EGR cooler is a reduction of the effectiveness due to the fouling layer primarily caused by thermophoresis, diffusion, and hydrocarbon condensation. Typically, effectiveness decreases rapidly at first, and asymptotically stabilizes over time. There are several hypotheses of this stabilizing phenomenon; one of the possible theories is a deposit removal mechanism. Verifying such a mechanism and finding out the correlation between the removal and stabilization tendency would be a key factor to understand and overcome the problem. Some authors have proposed that the removal is a possible influential factor, while other authors suggest that removal is not a significant factor under realistic conditions.

In this paper, a three-dimensional (3D) microstructure-based finite element modeling method (i.e., extrinsic modeling method) is developed, which can be used in examining the effects of porosity on the ductility/fracture of Mg castings. For this purpose, AM60 Mg tensile samples were generated under high-pressure die-casting in a specially-designed mold. Before the tensile test, the samples were CT-scanned to obtain the pore distributions within the samples. 3D microstructure-based finite element models were then developed based on the obtained actual pore distributions of the gauge area. The input properties for the matrix material were determined by fitting the simulation result to the experimental result of a selected sample, and then used for all the other samples’ simulation. The results show that the ductility and fracture locations predicted from simulations agree well with the experimental results.

This paper proposes a novel probabilistic approach for multidisciplinary design optimization (MDO) under uncertainty, especially for systems with feedback coupled analyses with multiple coupling variables. The proposed approach consists of four components: multidisciplinary analysis, Bayesian network, copula-based sampling, and design optimization. The Bayesian network represents the joint distribution of multiple variables through marginal distributions and conditional probabilities, and updates the distributions based on new data. In this methodology, the Bayesian network is pursued in two directions: (1) probabilistic surrogate modeling to estimate the output uncertainty given values of the design variables, and (2) probabilistic multidisciplinary analysis (MDA) to infer the distributions of the coupling and output variables that satisfy interdisciplinary compatibility conditions.

The internal combustion engine (ICE) is a typical complex multidisciplinary system which requires the support of precision design and manufacturing. To achieve a better performance of ICEs, tolerance assignment, or tolerance design, plays an important role. A novel multi-disciplinary tolerance design optimization problem considering two important disciplines of ICEs, the compression ratio and friction loss, is proposed and solved in this work, which provides a systematic procedure for the optimal determination of tolerances and overcomes the disadvantages of the traditional experience-based tolerance design. A bi-disciplinary analysis model is developed in this work to assist the problem solving, within which a model between the friction loss and tolerance is built based on the Gaussian Process using the corresponding simulation and experimental data.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

In an automotive cooling circuit, the wax melting process determines the net and time history of the energy transfer between the engine and its environment. A numerical process that gives insight into the mixing process outside the wax chamber, the wax melting process inside the wax chamber, and the effect on the poppet valve displacement will be advantageous to both the engine and automotive system design. A fully three dimensional, transient, system level simulation of an inlet controlled thermostat inside an automotive cooling circuit is undertaken in this paper. A proprietary CFD algorithm, Simerics-Sys®/PumpLinx®, is used to solve this complex problem. A two-phase model is developed in PumpLinx® to simulate the wax melting process. The hysteresis effect of the wax melting process is also considered in the simulation.

Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

Geometric Dimensioning and Tolerancing is used to describe the allowed feature variations regarding the product design. Tolerance specification is important in many stages of all phases on product development. The product development engineering need to define the symbols to use on the Feature Control Frame of every component. Since the component function has an increment on its complexity year over year, it is not trivial to define those symbols anymore. The determination of dimensional tolerance shall be preceded by careful specification of the types of tolerance and symbols that will be applied in controlled features. Poor tolerance specifications can increase the production cost, require late product changes or lead to legal issues.

Compression molded SMC composed of chopped carbon fiber and resin polymer which balances the mechanical performance and manufacturing cost presents a promising solution for vehicle lightweight strategy. However, the performance of the SMC molded parts highly depends on the compression molding process and local microstructure, which greatly increases the cost for the part level performance testing and elongates the design cycle. ICME (Integrated Computational Material Engineering) approaches are thus necessary tools to reduce the number of experiments required during part design and speed up the deployment of the SMC materials. As the fundamental stage of the ICME workflow, commercial software packages for SMC compression molding exist yet remain not fully validated especially for chopped fiber systems. In the present study, SMC plaques are prepared through compression molding process.

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this work, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. For multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance.

The introduction of carbon fiber reinforced polymer (CFRP) composites to structural components in lightweight automotive structures necessitates an assessment to evaluate that their crashworthiness dynamic response provides similar or higher levels of safety compared to conventional metallic structures. In order to develop, integrate and implement predictive computational models for CFRP composites that link the materials design, molding process and final performance requirements to enable optimal design and manufacturing vehicle systems for this study, the dynamic mechanical response of unidirectional (UD) and 2x2 twill weave CRFP composites was characterized at deformation rates applicable to crashworthiness performance. Non-standardized specimen geometries were tested on a standard uniaxial frame and an intermediate-to-high speed dynamic testing frame, equipped with high speed cameras for 3D digital image correlation (DIC).

For achieving viable mass customization of products, product configuration is often performed that requires deep understanding on the impact of product features and feature combinations on customers’ purchasing behaviors. Existing literature has been traditionally focused on analyzing the impact of common customer demographics and engineering attributes with discrete choice modeling approaches. This paper aims to expand discrete choice modeling through the incorporation of optional product features, such as customers’ positive or negative comments and their satisfaction ratings of their purchased products, beyond those commonly used attributes. The paper utilizes vehicle as an example to highlight the range of optional features currently underutilized in existing models. First, data analysis techniques are used to identify areas of particular consumer interest in regards to vehicle selection.

Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications.

The vehicle interior constitutes the multi-sensory environment of driver and passengers. Beside overall design and execution, materials and its surfaces are of specific interest to the customer. They are not only needed to fulfil technical functions, but are in direct focus of the customer’s perception. The perceived quality is based on all sensory data collected by the human perceptual system. Surfaces express design intent and craftsmanship by their visual appearance. Haptic features supervene when materials are touched. And even smell has an influence on the perception of ambience. Although sound is generated nearly every time when fingers slide across a surface, touch-sounds have been disregarded so far. In various cases, these contact sounds are clearly audible. As essential sound responses to haptic activity, they can degrade perceived quality. A method has been developed for a standardized generation of touch-sounds.

Thermally sprayed coatings have used in place of iron bore liners in recent aluminum engine blocks. The coatings are steel-based, and are sprayed on the bore wall in the liquid phase. The thermal response of the block structure determines how rapidly coatings can be applied and thus the investment and floor space required for the operation. It is critical not to overheat the block to prevent dimensional errors, metallurgical damage, and thermal stress cracks. This paper describes an innovative finite element procedure for estimating both the substrate temperature and residual stresses in the coating for the thermal spray process. Thin layers of metal at a specified temperature, corresponding to the layers deposited in successive thermal spray torch passes, are applied to the substrate model, generating a heat flux into the block. The thickness, temperature, and application speed of the layers can be varied to simulate different coating cycles.

Thermally sprayed engine bores require surface preparation prior to coating to ensure adequate adhesion. Mechanical roughening methods produce repeatable surfaces with high adhesion strength and are attractive for high volume production. The currently available mechanical roughening methods are finish boring based processes which require diameter-specific tooling and significant clearance at the bottom of the bore for tool overtravel and retraction. This paper describes a new mechanical roughening method based on circular interpolation. This method uses two tools: a peripheral milling tool, which cuts a series of concentric grooves in the bore wall through interpolation, and a second rotary tool which deforms the grooves to produce an undercut. This method produces equivalent or higher bond strength than current surface preparation methods, and does not require diameter-specific tooling or bottom clearance for tool retraction.

Tensile and fatigue properties of continuous braided carbon fiber reinforced polymer (CFRP) composite to AA6111 self-piercing riveted (SPR) lap shear joints are presented. Rivets were inserted at two target head heights separated by 0.3 mm. Even within the narrow range of head heights considered, the flushness of the rivet head was found to have a dominant effect on both the monotonic and fatigue properties of the lap shear SPR joints. Joints created with a flush head resulted in a greater degree of fiber breakage in the top ply of the CFRP laminate, which resulted in lower lap shear failure load as compared to SPR joints produced with a proud rivet head. Irrespective of the lap shear failure load, rivet pullout was the most common failure mode observed for both rivet head heights. In fatigue tests, the SPR joints produced with a proud head exhibited higher fatigue life compared to SPR joints produced with a flush head.

Designing a control system that can robustly detect faulted emission control devices under all environmental and driving conditions is a challenging task for OEMs. In order to gain confidence in the control strategy and the values of tunable parameters, the test vehicles need to be subjected to their limits during the development process. Complexity of modern powertrain systems along with the On-Board Diagnostic (OBD) monitors with multidimensional thresholds make it difficult to anticipate all the possible scenarios. Finding optimal solutions to these problems using traditional calibration processes can be time and resource intensive. A possible solution is to take a data driven calibration approach. In this method, a large amount of data is collected by collaboration of different groups working on the same powertrain. Later, the data is mined to find the optimum values of tunable parameters for the respective vehicle functions.