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Technical Paper

Heat Transfer Analysis of an Electric Motor Cooled by a Large Number of Oil Sprays Using Computational Fluid Dynamics

2022-03-29
2022-01-0208
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, 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.
Technical Paper

Modeling and simulation analysis of electric vehicle thermal management system based on distributed parameter method

2022-03-29
2022-01-0211
In this paper, the distributed parameter method is used to establish the dynamic simulation model of the electric vehicle thermal management system and various parts, and the finite difference method is used to solve the calculation. A thermal management system model for electric vehicles is established by AMESIM to verify the accuracy of the model established in this paper. The model established in this paper is compared with the change trend of refrigerant temperature, pressure and flow rate at the outlet of each component of the system calculated based on the model established by AMESIM, which verifies the correctness of the model established in this paper. Using the established model, the influence of the refrigerant flow on the cooling performance of the battery pack and the influence on the heating comfort of the passenger compartment were studied, and a control strategy for the rapid cooling of the battery pack was proposed.
Technical Paper

Multiphysics approach for thermal design of liquid cooled EV battery pack

2022-03-29
2022-01-0209
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. Liquid cooling techniques have proven to be cost-effective compared to other techniques such as air cooling, PCM-based in terms of performance in the given volumetric constraints. 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.
Technical Paper

Quantum Explanations for Destructive Interference in Engineering Decision Making

2022-03-29
2022-01-0215
Engineering practice routinely involves decision making under uncertainty. Much of this decision making entails reconciling multiple pieces of information. As more information is collected, one is expected to make better and better decisions. However, conditional probability assessments made by human decision makers, as new information arrives does not always follow expected trends and instead exhibits interference effects. Understanding such positive or negative interference of two or more information inputs is necessary for a better modeling of the cognitive processes taking place in the customer or the end user's mind. Doing so enhances the likelihood that better products and product features can be designed. Quantum probability has been used in the literature to explain many commonly observed deviations from classical probability. Some examples include: question order effect, response replicability effect, Machina and Ellsberg paradoxes.
Technical Paper

1D-3D Coupled Analysis for Motor Thermal Management in an Electric Vehicle

2022-03-29
2022-01-0214
Motor thermal management of electric vehicles (EVs) is becoming more significant due to its close relations to vehicle aerodynamic performance and energy consumption, while computer aided engineering (CAE) plays an important role in its development. A 1D-3D coupled model is established to characterize transient thermal performance of the motor in an electric vehicle on a high performance computer (HPC) platform. The 1D motor thermal management model is integrated with the 1D powertrain model, and a 3D thermal model is established for the motor, while online data exchange is realized between the 1D and 3D models. The 1D model gives boundaries such as inlet coolant temperature, mass flowrate and motor heat generation to the 3D model, while 3D gives back boundaries such as heat transfer to coolant simultaneously. Transient simulations are performed for the 140kph(20℃) driving cycle, and the model is calibrated with experimental data.
Technical Paper

Fault Diagnosis and Prediction in Automotive Systems with Real-Time Data Using Machine Learning

2022-03-29
2022-01-0217
In the automotive industry, a Malfunction Indicator Light (MIL) is a commonly employed to signify the failure or error in a vehicle system. To identify the root cause that has triggered a particular fault, a technician or engineer will typically run diagnostic tests and analyses. This type of analysis can take a significant amount of time and resources at the cost of customer annoyance and perceived quality. All modern vehicles generate data in the form of sensor readings accessible through vehicle Controller Area Network (CAN). This paper proposes the use of a recurrent neural network (RNN) to predict an impending fault before it occurs through the use of CAN data. Methods to pre-process the vehicle data for dimensionality reduction are proposed. The RNN then utilizes the processed data through short long-term memory to learn the system variables and input changes that contribute to the error over time.
Technical Paper

Design of a Human-centric Auto-Climate Control System for Electric Vehicles

2022-03-29
2022-01-0194
As the global automotive industry makes a critical transition from the traditional ICEVs (Internal Combustion Engine Vehicles) to EVs (Electric Vehicles), it faces two conflicting technological challenges: 1) range degradation in cold weather conditions and 2) reducing time to thermal comfort in winter driving in absence of waste heat from the IC engine. Next to the EV drivetrain, the HVAC system is the highest consumer of electric power in the vehicle. A recent study conducted by AAA showed that interior heating can reduce the EV range by up to 41% at 20 deg. F (https://apnews.com/article/04029bd1e0a94cd59ff9540a398c12d1). Also, in 2018, the average urban commute in the United States was roughly 27 minutes (https://www.washingtonpost.com/business/2019/10/07/nine-days-road-average-commute-time-reached-new-record-last-year/). So, it is necessary to get the driver to a thermally comfortable state as quickly as possible to make EVs attractive to consumers.
Technical Paper

Demonstrating UVC LED Inside Automobile HVAC Chambers for Clean Cabin Air and Airborne Transmission Risk Reduction

2022-03-29
2022-01-0197
The COVID-19 pandemic affected mobility in many ways- from changing business models of moving passenger to delivering packages and food, developing cleaning protocols for interiors and increasing the awareness of consumers to the hidden dangers of pathogens and viruses in an enclosed space. A trend towards healthy cars is believed to remain after the current pandemic and has led to the emergence of new safety features, from CO2 gas sensors, to antimicrobial fabrics, and enhanced air purifiers. While air purifiers trap contaminants using cartridge filters, they are not particularly efficient at removing viral particles and create large pressure drops, which must be compensated with larger fans, increasing noise and power consumption, both of which are not optimal for vehicle HVAC systems. However, air purifiers act as a pressure head, which limits their utility. UVC was not previously an option because mercury lamps pose their own electrical and chemical hazards.
Technical Paper

Use of Thermally Conductive Electrically Insulative (TCEI) Materials in E-motor Slot Liner Applications

2022-03-29
2022-01-0198
Slot liners are commonly used in electric motors to electrically insulate the motor windings from the laminated core. However, thermal conductivity of materials commonly used as slot liners is very low compared to other components in the motor thus creating a barrier for heat transfer. This thermal barrier affects overall motor performance and efficiency. Also, slot liners typically lack intimate contact with the laminated core resulting in air gaps which further increase thermal resistance in the system. Slot liners are traditionally made from high temperature films/papers that are cut and slid into slots of motors. The proposed work looks at developing an injection moldable slot liner to minimize air gaps. Additionally, use of TECI materials further lowers thermal resistance. A thermal finite element model has been developed to evaluate effects of slot liner thermal properties and air gaps on temperature distribution within the motor.
Technical Paper

Development of Vehicle Thermal Management Model for Improving the Energy Efficiency of Electric Vehicle

2022-03-29
2022-01-0201
Recently, automobile manufacturers are interested in the development of battery electric vehicle (BEV) having a longer mileage to satisfy customer needs. The BEV with high efficiency depends on the temperature of the electric components. Hence it is important to study the effect of the cooling system in electric vehicle in order to optimize efficiency and performance. In this study, we present a 1-D vehicle thermal management (VTM) simulation model. The individual vehicle subsystems were modeled including cooling, power electric (PE), mechanical, and control components. Each component was integrated into a single VTM model and it would be used to calculate energy transfer among electrical, thermal, and mechanical energy. As a result, this simulation model predicts a plenty of information including the state of each component such as temperature, energy consumption, and operating point about electric vehicle depending on driving cycles and environmental conditions.
Technical Paper

Influence of Material Anisotropy on Identification of Plane Strain Yield Strength of Automotive Sheet Metals using Inverse Analysis of Notch Tests

2022-03-29
2022-01-0241
Plane strain test specimens used for the constitutive characterization of automotive sheets are typically limited to low strains levels due to the onset of necking and fracture at the specimen edges in uniaxial tension. In contrast, notched plane strain tensile tests for fracture characterization are commonly used for the calibration of stress-state dependent fracture models and possess strong stress and strain gradients to avoid failure in uniaxial tension at the edges. Inverse finite-element analysis can be used to exploit the stress gradients in the notch test to calibrate the local arc of the anisotropic yield surface from uniaxial-to-plane strain tension. However, the principal stress directions across the width are not constant due to the notch geometry and can be influenced by the tensile properties in the other directions leading to non-unique solutions in the inverse analysis.
Technical Paper

A Novel Tensile Testing Method to Characterize the Weld Metal Properties for Laser Welded Blank (LWB) with AHSS

2022-03-29
2022-01-0243
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.
Technical Paper

Integrated Evaluation of Constant Amplitude Life Tests Towards SN Curves and Endurance Limit

2022-03-29
2022-01-0250
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 stair case 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 observations may be used for estimating the endurance limit or for the finite life re-gime. In this paper, we present an integrated approach, for simultaneous evaluation of both regimes. Every single ob-servation is mapped to one of the regimes with certain probabilities.
Technical Paper

Comparing stress gradient and other concepts for fatigue analysis of notched components

2022-03-29
2022-01-0252
Nowadays simulation of the fatigue life is an essential part of the development of components in the automotive and machinery industry. Weak points can be identified fast and reliable with respect to stiffness, strength and lightweight. A pure virtual optimization of the design can be performed without the need of prototypes. Only for the production release a final test is necessary. A lot of parameters influence the fatigue life as the local stress, material, surface roughness, size of the component, temperature etc. Notches have the strongest impact on fatigue life, depending on radius and shape. Stresses at the notch base are increased because the load flow is forced through a reduced cross section, or changes its direction around an inwardly curved edge. But notches cause not only an increase of the local stress. Also, the local fatigue strength is increased because of a support effect from the neighboring areas, where the stress is already reduced.
Technical Paper

Game Theory and Reinforcement Learning based Smart Lane Change Strategies

2022-03-29
2022-01-0221
With the development of science and technology, breakthroughs have been made in the fields of intelligent algorithms, environmental perception, chip embedding, scene analysis, and multi-information fusion, which together prompted the wide attention of society, manufacturers and owners of autonomous vehicles. As one of the key issues in the research of autonomous vehicles, the research of vehicle lane change algorithm is of great significance to the safety of vehicle driving. This paper focuses on the conflict of interest between the lane-changing vehicle and the target lane vehicle in the fully autonomous driving environment, and proposes the method of coupling kinematics and game theory and reinforcement learning based optimization, so that when the vehicle is in the process of lane changing game, the lane-changing vehicle and the target lane vehicle can make decisions that are beneficial to the balance of interests of both sides.
Technical Paper

Research on Vehicle State Segmentation and Failure Prediction Based on Big Data

2022-03-29
2022-01-0223
Vehicle failure prediction technology is an important part of PHM(Prognostic and Health Management) technology, which is of great significance to the safety of vehicles and to improve driving safety. Based on the vehicle operating data collected by the on-board terminal (T-box) of the telematics system, the research on the state of vehicle failure is conducted. First, this paper conducts statistical analysis on vehicle historical fault data. Preprocessing procedures such as cleaning, integration, and protocol are performed to group the data set. Then, three indexes including recency(R) frequency(F), and days(D) are selected to construct a vehicle security status subdivision system, and K -Means algorithm is utilized to divide different vehicle categories from the perspective of vehicle value. Labeled information of vehicles in different security status are further established.
Technical Paper

Early Detection of Engine Anomalies – A Case Study for AI-based Integrated Vehicle Health Management

2022-03-29
2022-01-0225
The increasing complexity of vehicle electronics and software is bringing an abundance of vehicle health related challenges, including quality issues and increasing costs of warranty claims, recalls, maintenance, and downtime. This negatively impacts both OEM and fleet profitability, user experience, and end customer costs. In order to reduce OEM costs and the total cost of ownership for consumers and fleets, new methods are needed to detect, predict, and diagnose vehicle health issues. Existing vehicle health management solutions rely on diagnostics trouble codes (DTC) and limited amounts of telematics data. These solutions can detect known failure modes using hard-coded signal behavior validation rules that are frequently based on thresholds. They also provide alerts based on pre-defined error codes. However, they are unable to detect and diagnose unforeseen failure modes that do not have hard-coded rules, nor can they prognose future vehicle health issues.
Technical Paper

Research on Local trajectory Planning and Control of Intelligent driving vehicle based on Particle Swarm Optimization

2022-03-29
2022-01-0224
Intelligent driving is an important research direction in the field of artificial intelligence. The fourth industrial revolution represented by the Internet of things provides more prospects for the development of intelligent vehicles. Trajectory planning and tracking control, as one of the key technologies of intelligent driving vehicles, has been widely concerned by industry and academia in recent years. In this paper, intelligent vehicle trajectory planning and tracking control are studied based on particle swarm optimization (Particle Swarm Optimization). The contents of the study are as follows: In the second chapter, the working principle of particle swarm optimization algorithm is introduced in detail. The algorithm is developed based on the behavior characteristics of bird foraging. On the basis of mastering the basic working principle of the algorithm, a trajectory planning method is proposed.
Technical Paper

Reinforcement learning enhanced New Energy Vehicle Dynamic Subsidy Strategies

2022-03-29
2022-01-0226
In recent years, game theory and reinforcement learning have become very popular research fields in today's society. As the most strategic analysis and optimization research method, they can be used in the study of subsidy strategy of China's new energy automobile industry to solve the problems caused by the government's subsidy of new energy vehicles. This paper studies the evaluation methods and strategy optimization methods of government subsidy strategies in different situations, and applies them to the subsidy strategies and other strategy optimization problems of new energy vehicles in China. Firstly, based on game theory, this paper studies the evaluation method of government subsidy strategy in the case of "double equivalence" and "one strong and one weak" by constructing the game process of "double equivalence" enterprises and "one strong and one weak" enterprises.
Technical Paper

Driver's driving style and driving condition recognition model based on SVM and XGBoost for online cloud platform

2022-03-29
2022-01-0227
At present, the remote monitoring cloud platform of many automobile companies only displays the collected data information, and it does not fully mine the deep-level information of the data. This paper uses data mining and machine learning methods to build a driver's driving style and driving condition prediction and recognition model based on the historical driving information generated by the vehicle, so as to improve the supervision and safety of the driver and the vehicle by automobile companies and other automobile-related industries. First, 36 standard driving cycles are utilized to construct an initial operating condition block data set. Second, we obtain the feature variables of driving style and driving conditions through feature engineering, and two recognition model data sets use the principal component analysis (PCA) and clustering algorithm for data dimensionality reduction and cluster analysis.
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