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Blow moulding is one of the most important polymer processing methods for producing complex thermoplastic automotive parts. Contrary to injection molding, little attention has focused on process control and simulation of blow molding processes. Yet, there are still several problems that affect the overall success of forming these parts. Among them are thermally induced stresses, relevant shrinkage and part warpage deformations caused by inappropriate mold design and/or processing conditions. Tolerance issues are critical in automotive applications and therefore part deformation due to solidification needs to be controlled and optimized accordingly. The accurate prediction tool of part deformation due to solidification, under different cooling conditions in automotive formed parts, is important and highly suited for part designers to help achieve an efficient production.

Ensuring durability is one of the key requirements while developing cooling modules for various powertrains. Typically, road surface induced loads are the main driving force behind mechanical failures. While developing the components, road load accelerations are utilized in CAE simulations to predict the high-stress regions and estimate the fatigue life of the components mounted on the body. In certain scenarios where components are mounted to the body and attached to the engine with hoses, the components can experience additional loads associated with engine vibration. This attachment scheme requires a different analysis methodology to determine fatigue life. In the proposed paper, we look at the effect of engine motion (EM) on the fatigue life of internal transmission oil cooler (ITOC) which is mounted on the body through radiator and is simultaneously connected to the engine using a steel pipe. We propose a new CAE methodology taking into account the engine motion displacements.

In this work, we outline a process for traffic light detection in the context of autonomous vehicles and driver assistance technology features. For our approach, we leverage the automatic annotations from virtually generated data of road scenes. Using the automatically generated bounding boxes around the illuminated traffic lights themselves, we trained an 8-layer deep neural network, without pre-training, for classification of traffic light signals (green, amber, red). After training on virtual data, we tested the network on real world data collected from a forward facing camera on a vehicle. Our new region proposal technique uses color space conversion and contour extraction to identify candidate regions to feed to the deep neural network classifier. Depending on time of day, we convert our RGB images in order to more accurately extract the appropriate regions of interest and filter them based on color, shape and size. These candidate regions are fed to a deep neural network.

This work describes a single camera based object distance estimation system. As technology on vehicles is constantly advancing on the road to autonomy, it is critical to know the locations of objects in 3D space for safe behavior of the vehicle. Though significant progress has been made on object detection in 2D sensor space from a single camera, this work additionally estimates the distance to said object without requiring stereo vision or absolute knowledge of vehicle motion. Specifically, our proposed system is comprised of three modules: vision based ego-motion estimation, object-detection, and distance estimation. In particular, we compensate for the vehicle ego-motion by using pin-hole camera model to increase the accuracy of the object distance estimation.

Radiator thermal cycle test is a test method to check out the robustness of a radiator. During the test, the radiator is going through transient cycles that include high and low temperature spikes. These spikes could lead to component failure and transient temperature map is the key to predict high thermal strain and failure locations. In this investigation, an accurate and efficient way of building a numerical model to simulate the transient thermal performance of the radiator is introduced. A good correlation with physical test result is observed on temperature values at various locations.

Degas bottles have been extensively used in vehicles in order to act as an air pillow on top of the cooling loop and provide space for expansion. One of the important characteristics of the bottle which defines if it will work in a certain loop is the so called “capacity” of the bottle which defines the flowrate that degas bottle would be able to pass through without any foaming. Considering the complex geometry of degas bottle and the foaming phenomena, predicting the behavior of coolant in the bottle passages is challenging which requires costly tests. Computational Fluid Dynamics (CFD) has been extensively used in simulating multi-phase flows in automotive components. In the current project, CFD has been used to simulate the behavior of flow in bottle chambers and to provide guidelines for the design team in order to increase the bottle performance/capacity. The CFD guidelines were in agreement with test results and lead to improving the degas bottle capacity.

An engine cooling system in an automotive vehicle comprises of heat exchangers such as a radiator, charge air cooler and oil coolers along with engine cooling fan. Typical automotive engine-cooling fan assembly includes an electric motor mounted on a shroud that encloses the radiator core. One of main drivers of fan shroud design is Noise, Vibration, and Harshness (NVH) requirements without compromising the main function of airflow for cooling requirements. In addition, there is also a minimum stiffness requirement of fan shroud which is often overlooked in arriving at optimal design of it. Low Speed Damageability (LSD) assessment of an automotive vehicle is about minimizing the cost of repair of vehicle damages in low speed crashes. In low speed accidents, these fan motors are subjected to sudden decelerations which cause fan motors to swing forward thereby damaging the radiator core. So designing fan shroud for low speed damageability is of importance today.

Heart rate is one of the most important biological features for health information. Most of the state-of-the-art heart rate monitoring systems rely on contact technologies that require physical contact with the user. In this paper, we discuss a proof-of-concept of a non-contact technology based on a single camera to measure the user’s heart rate in real time. The algorithm estimates the heart rate based on facial color changes. The input is a series of video frames with the automatically detected face of the user. A Gaussian pyramid spatial filter is applied to the inputs to obtain a down-sampled high signal-to-noise ratio images. A temporal Fourier transform is applied to the video to get the signal spectrum. Next, a temporal band-pass filter is applied to the transformed signal in the frequency domain to extract the frequency band of heart beats. We then used the dominant frequency in the Fourier domain to find the heart rate.

Centrifugal pumps are widely used in different thermal fluid systems in automobile industries. Computational fluid dynamics (CFD) analysis of such a thermal fluid system depends on the accurate component modeling of the system components. This paper presents CFD analysis of a centrifugal pump with two different approaches: Transient (moving grid) and the steady state - Multiple Reference Frame (MRF) methods using a commercial CFD solver Simerics MP+®. In addition, flow and pressure drop data obtained using CFD simulations of a vehicle coolant hydraulic system was compared to results from rig test data. The Transient method incorporates the real motion of the pump blades geometry and temporal flow solutions are obtained for instantaneous positions of the blade geometry. In MRF approach, the flow governing equations for the stationary zone are solved in the absolute/inertial reference frame, whereas flow in the moving zone is solved in the relative/non-inertial reference frame.

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.

As electrified powertrains proliferate through original equipment manufacturer vehicle offerings, the focus on system cost and weight reduction intensifies. This paper describes the development and evaluation of a High Voltage (HV) battery system enclosure molded from High Density Polyethylene (HDPE) to deliver substantial cost and weight opportunities. While previous HV battery system enclosure alternatives to steel and aluminum focus on thermoset composites and glass filled polypropylene, this solution leverages select HDPE design techniques established for fuel tanks and applies them to an HV battery system. The result is a tough, energy absorbing structure, capable of hermetic sealing, which simplifies manufacturing by eliminating nearly all fasteners.

In this article, the behavior of a typical air-to-air heat exchanger (intercooler) during the thermal shock test has been recorded during which the heat exchanger is exposed to very high temperature gradients. Different CAE models have been built that have different levels of details and the sensitivity of the results to the details has been studied. Finally a comparison have been made between the results of the CAE/CFD model and the experimental data and the correlation study shows that in spite of being simple, the dual stream is very accurate and correlates pretty well with test data. Including all design details in the CAE model will not necessarily improve the accuracy of the model while adding up to the computational cost.

Trapped air bubbles inside coolant systems have adverse effect on the cooling performance. Hence, it is imperative to ensure an effective filling and de-aeration of the coolant system in order to have less air left before the operation of the coolant system. In the present work, a coolant/air multiphase VOF method was utilized using the commercial CFD software SimericsMP+® to study the coolant filling and subsequent de-aeration process in a Battery Electric Vehicle (BEV) cooling system. First, validations of the numerical simulations against experiments were performed for a simplified coolant recirculation system. This system uses a tequila bottle for de-aeration and the validations were performed for different coolant flow rates to examine the de-aeration efficiency. A similar trend of de-aeration was captured between simulation and experimental measurement.