Search Results

This paper presents the design, implementation, and performance evaluation of a reduced complexity algorithm for a predictive control which is based on our previously published SAE paper (2021-01-0225) titled, “Model Predictive Control for Engine Thermal Management System.” That paper presented a model predictive control (MPC) design concept and demonstrated energy efficiency improvements by enabling engine pre-cooling based on GPS/Navigation data to recognize future vehicle speed limit and road grade in anticipation of high engine load demand. When compared to conventional control, the predictive control demonstrated considerable energy and fuel savings due to delayed timing of both knock mitigation and activation of radiator cooling fan during high engine load demand. However, this predictive control strategy is much more complicated due to its highly coupled nonlinear behavior.

Interest in electric vehicles (EVs) has significantly increased from the last decade, as the whole world is concerned about the reduction of emission of greenhouse gas by reducing the use of fossil fuel in transportation. The primary issue for electric vehicles is to develop an energy storage system i.e battery that can enable high mileage, rapid charging, and high-performance driving. Hence, battery management is required to get maximum, safe, and consistent performance of electric vehicles when running in a variety of conditions. To get the most out of a battery, it's important to keep an eye on its operating conditions, especially temperature, which has been shown to have a direct impact on battery performance and life. So, a battery thermal management system (BTMS) is crucial in the control of the thermal behavior of the battery. A good system simulation tool can minimize the time and cost of designing such a complicated thermal management system.

Thermal management of battery packs is essential to keep the cell temperatures within safe operating limits at all times and, hence, ensure the healthy functioning of an EV. The life cycle of a cell is largely influenced by its operating temperature, maintaining the cell temperature in its optimum range improves its longevity by decreasing its capacity fade rate and in turn extending the life of an EV. The battery thermal management solution being presented employs a tabbed type liquid cooling technology that achieves low-temperature differentials for an in-house designed battery pack consisting of 320 LFP cells (Size: 32700) with a total voltage and capacity of 27V and 240Ah respectively. Thermal design of the battery pack considers maximum dissipation when continuously operating at 1C-rate conditions. Furthermore, an intelligent methodology was adopted for higher reliability - cooling the entire battery pack from 50°C to 25°C within 30 min.

This paper reports on an analytical study of the heat transfer and fluid flow in an electric vehicle e-Motor cooled by twenty five sprays/jets of oil. A three-dimensional, quasi-steady state, multi-phase, computational fluid dynamics (CFD) and conjugate heat transfer (CHT) model was created using a commercial CFD software. The transport equations of mass, momentum, energy and volume fraction were solved together with models for turbulence and wall treatment. An explicit formulation of the volume of fluid (VOF) technique was used to simulate the sprays, a time-implicit formulation was used for the flow-field and three dimensional conduction heat transfer with non-isotropic thermal conductivities was used to simulate the heat transfer in the windings.

Designing an efficient vehicle coolant system depends on meeting target coolant flow rate to different components with minimum energy consumption by coolant pump. The flow resistance across different components and hoses dictates the flow supplied to that branch which can affect the effectiveness of the coolant system. Hydraulic tests are conducted to understand the system design for component flow delivery and pressure drops and assess necessary changes to better distribute the coolant flow from the pump. The current study highlights the ability of a complete 3D Computational Fluid Dynamics (CFD) simulation to effectively mimic a hydraulic test. The coolant circuit modeled in this simulation consists of an engine water-jacket, a thermostat valve, bypass valve, a coolant pump, a radiator, and flow path to certain auxiliary components like turbo charger, rear transmission oil cooler etc.

Aluminium alloy material cylinder head is a popular choice for any air-cooled internal combustion engine. But when it is exposed to higher temperature, it is vulnerable for its loss in strength. It becomes imperative to maintain cylinder head temperature well below acceptable temperature limit. Efficient cooling system play a vital role to achieve this objective. In the present work, an air-cooled diesel engine is converted into compressed natural gas (CNG) engine configuration for 25kVA genset configuration. A 1D gas-exchange model is created to generate the thermal boundary conditions required for Computational Fluid Dynamics (CFD) analysis. A steady-state 3D Conjugate Heat Transfer (CHT) model, that uses the predicted in-cylinder temperatures as a spatially varying boundary condition, is created to predict the convective heat transfer between engine fins and cooling air. A Blower Fan is modelled using the Moving Reference Frame (MRF) approach.

Plane strain tension is the critical stress state for sheet metal forming because it represents the extremum of the yield function and minima of the forming limit curve and fracture locus. Despite its important role, the stress response in plane strain deformation is routinely overlooked in the calibration of anisotropic plasticity models due to challenges and uncertainty in its characterization. Plane strain tension test specimens used for constitutive characterization typically employ large gage width-to-thickness ratios to promote a homogeneous plane strain stress state. Unfortunately, the specimens are limited to small strain levels due to fracture initiating at the edges in uniaxial tension. In contrast, notched plane strain tension coupons designed for fracture characterization have become common in the automotive industry to calibrate stress-state dependent fracture models. These coupons have significant stress and strain gradients across the gage width to avoid edge fracture.

In sheet metal testing, in-situ crack detection is either performed manually by purely visual inspection by the machine operator or automatically by a crack detection system. The automatic crack detection method, commonly integrated in sheet metal testing machines, evaluates the drawing force during forming. However, friction, vibration, and machine noise prevent reliable crack detection in thin sheets and foils. The same disturbance variables also prevent robust crack identification in thin sheets and foils by systems that analyze structure-borne sound. Crack detection systems that use reflected light methods, on the other hand, necessitate homogeneous illumination and are interfered by highly reflective as well as inhomogeneous sheet surfaces. In order to avoid the above-mentioned disadvantages of the currently existing crack detection methods, a procedure based on transmission-illumination was developed.

The automotive industry applies Laser Welded Blanks (LWB) to increase the material utilization and light-weighting of the vehicle structure. This paper introduces a novel tensile testing method to characterize the hardening behavior of the weld material with a digital image correlation (DIC) and apply it as a constitutive hardening model in forming simulations with the LWBs of GEN3 steel. Formability tests under biaxial conditions were performed with LWB of GEN3 steel. Experimental results were correlated with finite element analysis (FEA) predictions that were conducted with and without the weld material model. The results show the weld material model for the LWB improves the accuracy of FEA predictions of both necking failures on the base metal as well as cracking on the weld.

Limited room temperature formability hinders the wide-spread use of high strength aluminum alloys in body parts. Forming at warm temperatures or from softer tempers are the current solutions. In this work, our approach is to start with age-hardened sheets from 7xxx and 6xxx family of alloys and improve their formability using local thermomechanical processing only in the regions demanding highest ductility in the forming processes. We achieved local formability improvements with friction stir processing and introduce another process named roller bending-unbending as a concept and showed its feasibility through finite element simulations. Initial results from FSP indicated significant deformation in the processed zones with minimal sheet distortion. FSP also resulted in dynamically recrystallized, fine grained (d < 5 μm) microstructures in the processed regions with textures significantly different from the base material.

Soft magnetic lamination core is a major component of electric motors. The magnetic quality of the lamination has a significant effect on the energy efficiency of the motor. The magnetic properties of electrical steel sheets, which are important design parameters for the manufacturing of electric motors, are normally measured on cut steel strips by standard Epstein frame method, which is destructive and not suitable for the evaluation of magnetic anisotropy. In this paper, magnetic Barkhausen noise (MBN) analysis is used to evaluate the magnetic quality of electrical steel sheets. This method is featured by non-destructive, simple measurement, short measuring time, and offline/online measurements, etc. In addition, it can be readily used to estimate the magnetic anisotropy in all directions of the electrical steel sheet.

During deep drawing processes, the metal blank is radially drawn by mechanical action of the punch forcing the metal into a forming die. As a result, the workpiece goes through some work hardening where some residual energy is released in final stage which results in further deformation of the part (so called “springback”). This research paper is focused on development of a real-time control strategy to reduce springback effects in deep drawing. It reports on the results of the experimental study of springback in drawing and the parameters involved. In this regard, an experimental setup is designed and developed that is used for design of experiment study and simulation validation of the process. Design of experiment technique is utilized to systematically analyze the effects of the process parameters and their relative contribution in springback phenomenon.

This study focuses on variable amplitude loadings applied to automotive chassis parts experiencing carmaker’s specific proving grounds. They are measured with respect to time at the wheel centres and composed of the six forces and torques at each wheel, within the standard vehicle reference frame. In the scope of high cycle fatigue, the loadings considered are supposedly acting under the structure yield stress. Among the loadings encountered during the vehicle lifetime, two classes stand out: Driven Road: loads measured during the vehicle manoeuvre; Random Road: loads mainly coming from the road asperity. To separate both effects, a frequency decomposition method is proposed before applying any lifetime assessment methods. The usual Rainflow counting method is applied to the Driven Road signal. These loadings, depending on the vehicle dynamics, are time-correlated. Thus, the load spectra is set only thanks to the vehicle accelerations time-measurement.

As the international community strengthens the control of carbon dioxide emissions, electric vehicles have gradually become a substitute for internal combustion engine vehicles. The battery pack is one of the most important components of electric vehicles. The strength and fatigue performance of the battery support plate not only affect the performance of the vehicle but also concern the safety of the driver. In the present study, the finite element model of a battery pack for fatigue analysis is completely established. The random vibration stress response analysis and acceleration power spectral density response analysis of the support plate for the battery pack are carried out, and the accuracy of the finite element model is verified by a random vibration test.

In automotive body manufacturing the dies for blanking/trimming/piercing are under most severe loading condition involving high contact stress at high impact loading and large number of cycles. With continuous increase in sheet metal strength, the trim die service life becomes a great concern for industries. In this study, competing trim die manufacturing routes were compared, including die raw materials produced by hot-working (wrought) vs. casting, edge-welding (as repaired condition) vs. bulk base metals (representing new tools), and the heat treatment method by induction hardening vs. furnace through-heating. CaldieTM, a Uddeholm trademarked grade was used as trim die material. The mechanical tests are performed using a WSU developed trimming simulator, with fatigue loading applied at cubic die specimen’s cutting edges through a tungsten carbide rod to accelerate the trim edge damage. The tests are periodically interrupted at specified cycles for measurement of die edge damage.

The emergence of additive manufacturing (AM) technology has enabled the internal cooling channel layout for high pressure aluminium die casting (HPADC) tools to be designed and modified without topological constraint. Optimisation studies of a full industrial HPADC mould for extending the tool service life has received limited attention due to the high geometrical complexity and the various physics with multi time- and length- scales in addition to the manufacturability limitations. In this work, a new computationally efficient algorithm that employs the adjoint optimisation method has been developed to optimise the coolant channels layout in a complete mould with various 3D printed inserts. The algorithms significantly reduced the computational time and resources by decoupling the fluid flow in the coolant channels from the tool and simulating them separately.

Establishing SN curves from constant amplitude life tests and locating the endurance limit are indispensable tasks in durability engineering. For both regimes, finite life and endurance limit, there are many approaches available, like linear regression or maximum likelihood. Especially on low load levels, tests may run very long and one may suspend them before failure. Especially the staircase method for evaluating the endurance limit systematically produces almost 50 percent suspended results. Hence, when data for both regimes is available, those run-outs need to be considered in a statistically proper way. If both regimes are evaluated separately it is often ambiguous if a single observation may be used for estimating the endurance limit or for the finite life regime. In this paper, we present an integrated approach, for simultaneous evaluation of both regimes. Every single observation is mapped to one of the regimes with certain probabilities.

The diminutive rolling resistance and wheel bearing drag characteristics of a bicycle wheel assembly make it a lucrative choice of component in numerous 3-wheeled (3W) and 4-wheeled (4W) automotive applications. However, when a bicycle wheel is subjected to the loads encountered in such applications, complications pertaining to strength, durability and, performance are encountered. Since a bicycle wheel is intended to be arrested at either end of its axle, cantilever loading of the component, as practiced in automotive applications, diminishes the ability of the spindle to withstand longitudinal and vertical forces encountered. Furthermore, while cornering on a bicycle, the maneuver of leaning in a corner significantly reduces the lateral stiffness requirement of the hub flanges. Therefore generic hub assemblies are designed without accounting for the action of lateral forces that are experienced at the hub with the wheel held vertical.

This paper describes a new procedure for more accurate durability predictions of stress along edges of automotive body structures. The current elemental stress based CAE procedures often require iterative mesh refinement to correlate predictions to experimental cracking on the edges of components. The new proposed procedure is based on element nodal stress. It is first studied on a circular hole representing a notch in a rectangular plate with different element sizes and options. Elemental nodal stress demonstrates an improvement over elemental stress methods by correlating with theoretical notch stress result. The proposed procedure is then studied on multiple examples of experimental cracks and successfully predicts issues where the current elemental stress method does not. In addition, it avoids the iterative mesh refinement associated with the current methods.

This study investigated the plastic deformation behavior of 304 stainless steel thin-walled tubes under axial compression by means of numerical calculation and theoretical analysis. It was found that the plastic deformation length of thin-walled tube determined the formability of folds and the work done in the whole axial compression process. To reveal the relation between the range of plastic deformation length and tube geometry parameters, regression equations were established using the quadratic regression orthogonal design method. Experiments were conducted to validate the equations. The process windows for forming a single fold and tube joining at ends had been printed ultimately. The results showed that the regression equations can accurately predict the range of plastic deformation length for forming a single fold.