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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

ANALYSIS OF THE CURRENT TRENDS IN DEVELOPMENT ACCELERATED TESTING

2022-03-29
2022-01-0212
Analysis of the Current Trends in Development Accelerated Testing In 2020 ELSEVIER published author's book "Trends in Development Accelerated Testing for Automotive and Aerospace Engineering". As featured on CNN, Forbes, and Inc - BookAuthority, identifies and rates the best books in the Word based on recommendations by thought leaders and experts, this book made it to BookAuthority's best aerospace Engineering books (#43) and best Automotive Engineering books (#14) of all times (see "100 Best Aerospace Engineering Books of All Times" and "52 Best Automotive Engineering Books of All Times"). This paper will discuss the continuation - trends in development accelerated testing as result of the analysis current situation (2019 - 2021) on examples of automotive and aerospace areas. As was mentioned in the previous author's publications, the technical progress of product's testing is moving much slowly, then the technical progress in design, manufacturing, and service areas of the product.
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

Driving Behaviour Analysis Software for Data-Driven Path Planning Functionalities for Automated Vehicles

2022-03-29
2022-01-0218
Autonomous driving is currently one of the most challenging Artificial Intelligence (AI) problems as it requires combination of state-of-the-art solutions in multiple areas including computer vision, sensor fusion, control theory and software engineering. Deep learning has been pivotal to solving some of these problems, especially in computer vision. This enabled some autonomous vehicle companies started leveraging the benefits of deep learning for creating smooth, natural, human-like motion planning systems. In particular, the plethora of driving data captured from modern cars is a key enabler for training data-driven path planning systems. , Developing deep learning-powered systems relies heavily on big and high-quality data required for training of the models, in which the intrinsic statistics of the data that the model is trained on can result in different agent behavior in different scenarios.
Technical Paper

Fatigue Damage of Trim Dies Manufactured or Reconditioned by Different Routes

2022-03-29
2022-01-0245
The compression fatigue behavior of sheet metal trimming die is studied. The trim dies were manufactured or reconditions through different fabrication processes and heat treatment conditions. An accelerated lab testing method is developed to evaluate die damage resistance under compressive cyclic load applied at the tool edge, analogous to sheet metal trimming die operation. The metal removal volume at the sheared edges were measured by image processing to quantify the degree of fatigue damage as a function of loading cycle number. The fatigue microstructural damage were examined with optical and scanning electron microscopies. The simulated die performances are compared among different die processing routes. A phenomenological trim die damage rate model in Paris law form was obtained and tuned with experimental data for tool life prediction.
Technical Paper

Natural rubber life estimation through an extreme learning machine

2022-03-29
2022-01-0251
In engineering applications, rubber isolators are subjected to continuous alternating loads, resulting in fatigue failure. Although some theoretical models are used for the fatigue life estimation of rubber materials, they do not comprehensively consider the influences of multiple factors. In the present study, a model based on the extreme learning machine (ELM) is established to estimate fatigue life of natural rubber (NR) specimens. The mechanical load (engineering strain peak), ambient temperature (23℃, 60℃ and 90℃) and shore hardness (N45 and N50) of NR specimens are used as the input variables while the measure average fatigue life as the output variable of the ELM. The regression results and predicted life distribution of the established ELM model are encouraging. For comparison, the back propagation neural network (BPNN) model and the support vector machine (SVM) model are also implemented.
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

Modern Product Development Platform for Living Products in Perpetual Systems

2022-03-29
2022-01-0230
In 1930, John Maynard Keynes predicted, that due to software and automation, 15-hour work weeks would be a reality by the end of the century. While that envisioned “utopia” has not been realized, Mr. Keynes did have the radical vision to imagine a pretty radical low code highly automated future - one to which the future of software in mobility arguably depends on. So, what went wrong? Well, its not about as much about what went wrong but about how adoption is taking place and how it needs to change. In any software development, no matter where in history, as soon as software testing became a hot topic, automation tools started springing up and then "selective parts" that were iterative and time-consuming in the software were automated away. This begs several questions. The first and obvious, why automate these parts - and the second - whether software developers are making themselves obsolete by building automation tools.
Technical Paper

Direct Alert to In-Vehicle Infotainment (DAIVI)

2022-03-29
2022-01-0231
Nowadays, the mobile phone features are widely used by drivers to get the notifications and alerts on the head unit. However, there are no available products in the market to get important notifications in Head units without the use of mobile phones. There are many important notifications that are critical for a user when he is away from home. Some of them are alerts from home security systems, smoke and gas detection alarms etc. Most of the existing systems push alerts to customer mobile phones. In this paper, the authors propose a concept to direct the alerts to In-Vehicle Infotainment systems. Proposed here is a new approach, Direct Alert to In-Vehicle Infotainment (DAIVI), in which the infotainment head unit will be able to get the notification or alerts without using a mobile phone. The DAIVI complements the existing systems of alerts to the user by using in-vehicle infotainment for alerting on the critical issue.
Technical Paper

Future of Autonomous Vehicles: Autonomy as Service

2022-03-29
2022-01-0232
The functional blocks of an autonomous vehicle can be divided into four fundamental blocks: (1) Sensing and Connectivity; (2) Perception and Situational Awareness; (3) Planning and Behaviors and (4) Vehicle Control. In general, one can picture the data flow beginning at the sensing and connectivity block were either raw data from sensors and/or data from wireless connected devices stream into the vehicle’s network. The data rates associated with this raw data can be enormous: over 10Gbps. Hence the data is often locally processed to render manageable data sets that are used in the Perception and Situation Awareness Block. The data rates become very reasonable, under 2Mbps, with acceptable latencies of approximately 20msec. This data is then processed by the Planning and Behaviors Block the develops the best path and trajectory for the vehicle.
Technical Paper

A Perspective on Materials Selection for Body Structure Lightweighting in Battery Electric Vehicles

2022-03-29
2022-01-0233
The secular trend of automotive body structure light-weighting for internal combustion engine (ICE) vehicles is constrained by simultaneous and increasingly challenging vehicle cost, fuel economy and passenger safety standards. Mass optimization via materials selection in ICE vehicles, therefore, is ultimately dependent on the normalized cost of mass reduction solutions and the associated implications on passenger safety and vehicle performance metrics. These constraints have resulted in development and implementation of increasingly high specific-strength solutions for metallic components in the body structure and chassis. In contrast, mass optimization in battery electric vehicles is subject to alternative performance metrics to fuel efficiency, although considerations for vehicle safety and cost naturally remain directionally similar.
Technical Paper

Technical Keynote: Durability Validation for Variable Vehicle Usage

2022-03-29
2022-01-0255
Durability engineering for vehicles is about relating real operational loading to the actual strength of the product and its components. In the first part of this presentation, we show how to calculate failure probabilities and safety factors based on the load and strength distributions. We discuss the uncertainty within the estimations, which is considerably large in case of extremely small failure probabilities as required for safety critical components. In the second part, we focus on modelling and simulating the loads based on real vehicle usage, such that the resulting statistics allows to understand and quantify the usage variability. The idea is, to simulate thousands of vehicle life spans of, say, 300.000 km or 15.000 h of operation each. The input data for such simulations typically consists of a combination of geographic data (like road network, topography, road conditions, traffic data, and points of interest) and properly segmented rich data from measurement campaigns.
Technical Paper

Numerical Investigation on the Internal Flow Field of Electronic Expansion Valve as the Throttle Element

2022-03-29
2022-01-0318
As one of the key components of the heat pump system, the electronic expansion valve mainly plays the role of throttling and reducing pressure in the heat pump system. The refrigerant flowing through the orifice will produce complex phase change. It is of great significance to study the internal flow field by means of CFD calculations. Firstly, a three-dimensional fluid model is established and the mesh is divided. Secondly, the phase change model is selected, the material is defined and the boundary conditions are determined. According to the principle of the fluid passing through thin-walled small holes, the flow characteristics of electronic expansion valve are theoretically analyzed. Then the flow characteristics of expansion valve are numerically calculated, and a bench for testing mass flow rate of the expansion valve is built. Then the theoretical value, CFD value and experimental value are compared to verify the correctness of the established three-dimensional fluid model.
Technical Paper

Development of FE modeling Procedures for Laser Welded Aluminum Structures in An Electric Vehicle Battery Module and Validation by Test Data

2022-03-29
2022-01-0317
High strength and thin materials are widely adopted in modern electric vehicles for lightweight design to achieve high energy efficiency. For battery modules, 5000 and 6000 aluminum are typically utilized as a structural material with a thickness range between 1 to 5 mm. Laser welding is one of the most optimum welding tools for joining such a thin material due to its unique advantages, e.g., high welding speed, high accuracy, high energy yet the smallest possible heat affect zone, etc. This paper aims to develop a simplified yet effective FE modeling procedure to simulate the laser welding effects on the aluminum structures used in electric vehicle battery modules. A sequentially-coupled thermo-mechanical analysis procedure is developed to determine the softened zone size for aluminum weldments. Then a tie-rupture weld model incorporates the softened zone to predict the weld failure strength.
Technical Paper

Parameter Analysis and Optimization of Road Noise Active Control System

2022-03-29
2022-01-0313
The parameter setting has a great influence on the noise reduction performance of the road noise active control (RNC) system. This paper analyzes and optimizes the parameters of the RNC system. Firstly, the model of the RNC system is established based on the FxLMS algorithm. Based on this model, taking the maximum noise reduction as the evaluation index, the sensitivity analysis of convergence coefficient, filter order, and reference signal gain was carried out using the Sobol method with the data measured by a real vehicle on asphalt pavement at 40km/h. The results show that there is no significant interaction between the three parameters. Then, using the idea of orthogonal experiment, the simulation results of the control model are analyzed by taking the maximum noise reduction as the evaluation index. It is found that the convergence coefficient has the greatest effect on the maximum noise reduction, followed by the filter order, and the reference signal gain has the least effect.
Technical Paper

Innovative vehicle battery pack design approach through multiphysics cells simulation

2022-03-29
2022-01-0267
This paper presents the design procedure of a vehicle battery pack, in terms of electrical and mechanical requirements with an innovative methodology to model Li-ion cells’ thermo-electro-mechanical behaviour. This modelling approach can predict, through FEM analysis, if short circuit happen with consequent generation of fire in case of vehicle crash. This last aspect has several issues related to the multiphysics characteristics of the phenomena due to the fact that battery cells are made up by really thin components and, as consequence, not significant works of an entire deformable battery pack simulation have been found in literature. For this reason, the design approach studied overcomes the classical methodology in which cells’ mechanical behaviour is considered unknown to understand if cell failure appears avoiding over-engineered battery pack structure. At the beginning, a benchmarking activity on existing FEM modelling methodologies of single cells has been conducted.
Technical Paper

Investigation of Heat Transfer Characteristics of Heavy-Duty Spark Ignition Natural Gas Engines Using Machine Learning

2022-03-29
2022-01-0473
Machine learning algorithms are effective tools to reduce the number of engine dynamometer tests during internal combustion engine development and/or optimization. This paper provides a case study of using such a statistical algorithm to characterize the heat transfer from the combustion chamber to the environment during combustion and during the entire engine cycle. The data for building the machine learning model came from a single cylinder compression ignition engine (13.3 compression ratio) that was converted to natural-gas port fuel injection spark-ignition operation. Engine dynamometer tests investigated several spark timings, equivalence ratios, and engine speeds, which were also used as model inputs. While building the model it was found that adding the intake pressure as another model input improved model efficiency.
Technical Paper

A New Pathway for Prediction of Gasoline Sprays using Machine-Learning Algorithms

2022-03-29
2022-01-0492
The fuel spray process is of utmost importance to internal combustion engine design as it determines engine performance and emissions characteristics. While designers rely on CFD for understanding of the air-fuel mixing process, there are recognized shortcomings in current CFD spray predictions, particularly under super-critical or flash-boiling conditions. In contrast, time-resolved optical spray experiments have now produced datasets for the three-dimensional liquid distribution for a wide range of operating conditions and fuels. Utilizing these detailed experimental results, we have explored a machine learning approach to prediction of fuel sprays. The ML approach for spray prediction is promising because (1) it does not require phenomenological spray models, (2) it can provide time-resolved spray data without time-stepping simulation, and (3) it is computationally faster than CFD. In this study, a pixel-regression model has been developed and applied for gasoline spray prediction.
Technical Paper

Laser-Based In-Exhaust Gas Sensor for On-Road Vehicles

2022-03-29
2022-01-0535
Indrio Technologies has developed a novel on-board sensor, named Ignis, for detecting oxides of nitrogen (NOx) and ammonia (NH3) in diesel exhaust streams with sensitivities and molecular specificity unmet by existing technologies. This is a key technological need for diesel engine manufacturers, who face difficulty in precisely controlling their exhaust aftertreatment systems due to the lack of widely deployable sensors capable of differentiating between NOx, NH3 and other species in the exhaust stream. The successful incorporation of the proposed sensor can result in greater fuel efficiency improvements while matching new stringent 2027 California and 2030 EPA NOx emissions standards. Once the product has reached deep market penetration, the fleet-wide fuel economy improvements and NOx emissions reductions enabled by this product will lead to reduced carbon emissions and healthier air with lower amounts of NOx-induced smog, ground-level ozone, and acid rain.
Technical Paper

Fast Air-Path Modeling for Stiff Components

2022-03-29
2022-01-0410
Development of powertrain control systems frequently involves large-scale transient simulations, e.g. Monte Carlo simulations or drive-cycle optimizations, which require fast dynamic plant models. Models of the air-path—for internal combustion engines or fuel cells—can exhibit stiff behavior, though, causing slow numerical simulations due to either using an implicit solver or sampling much faster than the bandwidth of interest to maintain stability. This paper proposes a method to reduce air-path model stiffness by adding an impedance in series with potentially stiff components, e.g. throttles, valves, compressors, and turbines, thereby allowing the use of a fast-explicit solver. An impedance, by electrical analogy, is a frequency-dependent resistance to flow, which is used to suppress the high-frequency dynamics causing air-path stiffness, while maintaining model accuracy in the bandwidth of interest.
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