Browse Topic: Calibration

Items (1,665)
Path tracking control, which is one of the most important foundations of autonomous driving, could help the vehicle to precisely and smoothly follow the preset path by actively adjusting the front wheel steering angle. Although there are a number of advanced control methods with simple structure and reliable robustness that could assist vehicles achieving path tracking, these controllers have many parameters to be calibrated, and there is a lack of guidance documents to help non-professional test site engineers quickly master calibration methods. Therefore, this paper proposes a parameter virtual calibration method based on the deep reinforcement learning, which provides an effective solution for parameter calibration of vehicle path tracking controller. Firstly, the vehicle trajectory tracking model is established through the kinematic relationship between the vehicle and the target path, combined with the Taylor series expansion linearization method. Next, a vehicle path tracking
Zhao, JianGuo, ChenghaoZhao, HuiChaoZhao, YongqiangYu, ZhenZhu, BingChen, Zhicheng
Motor drive control is crucial for achieving the performance, reliability, and comfort of electric vehicles. Multi-phase motors, represented by dual-winding permanent magnet synchronous motors (PMSMs), have significant research value in the electric vehicle field due to their high-power drive capabilities and strong fault tolerance. A simple and easily analyzable motor model is essential for achieving high precision in control. This paper employs VSD coordinate transformation (vector space decomposition) based on electromagnetic principles and the positional relationships between windings, treating the multi-phase motor as a whole and mapping various physical quantities to multiple subspaces for simplified analysis. Consequently, a mathematical model for the dual-winding PMSM is established. The vector control system based on VSD coordinate transformation adopts a dual closed-loop structure for speed and current. It focuses on a comparative analysis between traditional two-vector
Gao, ChaoFanZheng, HongyuKaku, Chuyo
The performance of a second-generation Toyota Mirai fuel cell was characterized as part of the SwRI internal research program. This data was used to develop a supervisory controller scheme designed to balance the plant for the fuel cell system during steady-state and transient vehicle conditions. This was accomplished using a Supervisory Integrated Controller (SIC) implemented on a Real-time Power Electronics Control System (RPECS) with a Simulink-based control algorithm. The actuators of interest are the three hydrogen injectors at anode inlet, air compressor and three air side valves on at the cathode inlet. The FC power measurement and pressure sensor readings at the anode and cathode were utilized as real-time feedback for the controller operation. The aim of the controller was to achieve and maintain the power target set by the hybrid powertrain ECU present on the vehicle, which is responsible for balancing power on the fuel cell and battery over the high-voltage bus. These
Chundru, Venkata RajeshKubesh, MatthewLegala, Adithya
One challenge for autonomous vehicle (AV) control is the variation in road roughness which can lead to deviations from the intended course or loss of road contact while steering. The aim of this work is to develop a real-time road roughness estimation system using a Bayesian-based calibration routine that takes in axle accelerations from the vehicle and predicts the current road roughness of the terrain. The Bayesian-based calibration method has the advantage of providing posterior distributions and thus giving a quantifiable estimate of the confidence in the prediction that can be used to adjust the control algorithm based on desired risk posture. Within the calibration routine, a Gaussian process model is first used as a surrogate for a simulated half-vehicle model which takes vehicle velocity and road surface roughness (GD) to output the axle acceleration. Then the calibration step takes in the observed axle acceleration and vehicle velocity and calibrates the Gaussian process model
Lewis, EdwinaParameshwaran, AdityaRedmond, LauraWang, Yue
Wind tunnel calibration is necessary for repeatable and reproducible data for all industries interested in their output. Quantities such as wind speed, pressure gradients, static operating conditions, ground effects, force and moment measurements, as well as flow uniformity and angularity are all integral in an automotive wind tunnel’s data quality and can be controlled through appropriate calibration, maintenance, and statistical process control programs. The purpose of this technical paper is to (1) provide a basis of commonality for automotive wind tunnel calibration, (2) help customers and operators to determine the calibration standards best suited for their unique automotive wind tunnel and, (3) complement the American Institute of Aeronautics and Astronautics recommended practice R-093-2003(2018) Calibration of Subsonic and Transonic Wind Tunnels as specifically applied to the automotive industry. This document compiles information from various automotive wind tunnel customers
Bringhurst, KatlynnBest, ScottNasr Esfahani, VahidSenft, VictorStevenson, StuartWittmeier, Felix
This paper focuses on the development of a tire thermal model for automotive applications, addressing the challenge of accurately predicting tire temperatures on different layers of the tire, under various driving conditions. The primary goal is to enhance the understanding of tire temperature behavior to improve safety, performance, and durability. The research utilizes a physics 1-D model for the tire, from which a system of differential equations, describing the interaction between different layers of the tire, is derived. Furthermore, a state observer is used to estimate tire temperatures, using Tire Pressure Monitoring System (TPMS) measurements to correct model predictions. In particular, the TPMS measurements are assumed to be sufficient to exclude the additional thermal contributions coming from the rims and disk brakes, which simplifies the model, making it more suitable for real-time applications. A calibration procedure is defined for deriving the model parameters, based on
Longobardi, ArmandoBalaga, Sanjaylabella, MarioGorine, Mohamed El Amine
This paper focuses on the basic principle of measuring viscosity and density with U-shaped tungsten wire sensor, and develops a model for measuring liquid viscosity and density with the help of oscillating ball model. Firstly, the working mechanism of the wire resonator is deeply analyzed. Then, by reducing the order of the fluid dynamic function, a simplified model is established for measuring the viscosity and density of liquid with U-shaped tungsten resonator. The experimental results show that the maximum error of viscosity is 7.22% and the average error is 2.81% when the viscosity ranges from 4.526mPa.s to 62.01mPa.s. In the range of 0.8486g/cm3 to 0.8711g/cm3, the maximum density error is 7.00% and the average density error is 1.89%. In summary, the simplified model proposed in this paper can accurately measure the viscosity and density of liquids.
Shan, BaoquanShen, YitaoYang, JianguoZhang, ZhaoyingWu, DehongZhao, Yingke
High-speed railway (HSR) hubs play a pivotal role in the integrated transport system, efficiently connecting various modes of transport and facilitating transport integration. Characterized by their large scale, complex functional spatial layouts, and diverse interchange types, these hubs see a growing proportion of passenger traffic annually. Thus, studying the interchange impedance in high-speed railway passenger transport hubs is crucial for enhancing interchange efficiency and service quality. However, current research lacks a quantitatively comparable impedance model for high-speed railway hubs, particularly under peak passenger flow conditions. This paper addresses this gap by examining the internal node impedance at Nanjing South Railway Station, focusing on the entry gate turnstile node and security check node. It begins by analyzing passenger passing behavior at these nodes and then constructs a integrated queuing model for inbound gates and security checks, considering the
Zhang, ZhenyuWang, Jian
Vehicle localization in enclosed environments, such as indoor parking lots, tunnels, and confined areas, presents significant challenges and has garnered considerable research interest. This paper proposes a localization technique based on an onboard binocular camera system, utilizing binocular ranging and spatial intersection algorithms to achieve active localization. The method involves pre-deploying reference points with known coordinates within the experimental space, using binocular ranging to measure the distance between the camera and the reference points, and applying the spatial intersection algorithm to calculate the camera’s center coordinates, thereby completing the localization process. Experimental results demonstrate that the proposed algorithm achieves sub-meter level localization accuracy. Localization accuracy is significantly influenced by the calibration precision of the binocular camera and the number of reference points. Higher calibration precision and a greater
Feifei, LiHaoping, QiYi, Wei
This study presents a method to evaluate the daily operation of traditional public transportation using multi-source data and rank transformation. In contrast with previous studies, we focuses on dynamic indicators generated during vehicle operation, while ignoring static indicators. This provides a better reference value for the daily operation management of public transport vehicles. Initially, we match on-board GPS data with network and stop coordinates to extract arrival and departure timetable. This helps us calculate dynamic operational metrics such as dwell time, arrival interval, and frequency of vehicle bunching and large interval. By integrating IC card data with arrival timetable, we can also estimate the number of people boarding at each stop and derive passenger arrival time, waiting time, and average waiting time. Finally, we developed a comprehensive dynamic evaluation method of public transportation performance, covering the three dimensions: bus stops, vehicles, and
Zhou, YangShao, YichangHan, ZhongyiYe, Zhirui
This SAE Aerospace Recommended Practice (ARP) provides recommended practices for the calibration and acceptance of icing wind tunnels to be used in testing of aircraft components and systems and for the development of simulated ice shapes. This document is not directly applicable to air-breathing propulsion test facilities configured for the purposes of engine icing tests, which are covered in AIR6189. This document also does not provide recommended practices for creating Supercooled Large Drop (SLD) or ice crystal conditions, since information on these conditions is not sufficiently mature for a recommended practice document at the time of publication of ARP5905A. Use of facilities as part of an aircraft’s ice protection Certification Plan should be reviewed and accepted by the applicable regulatory agency prior to testing. Following acceptance of a test plan, data generated in these facilities may be submitted to regulatory agencies for use in the certification of aircraft ice
AC-9C Aircraft Icing Technology Committee
Throughout the years, the legislations which drive the vehicle development have experimented constant evolutions. Especially when it comes about pollutant emissions and NVH ( Noise, Vibration & Harshness). However, it is complex to understand which calibration strategy promotes the best balance about lowest levels of emissions, vibrations, and noise if considered the number of inputs to be explored, becoming the searching for the optimum calibration a huge challenge for the development engineering team. This work proposes a methodology development in which complex problems can be solved by model based solutions regarding the best balance finding of emissions reduction and noise attenuation. The methodology is based in machine learning approach which provides a virtual behavior of engine phenomena making possible a wider comprehension of the problem and hence the opportunity to explore enhanced solutions. The study case scenario used to apply the method was a 6.4 liters engine which
Ruiz, Rodrigo Peralta MoraesSantos, Lucas ResendeNascif, Gabriel Nobre AlvesOliveira Ribeiro, DouglasPereira, Willyan
This research introduces a Detailed Digital Fuel Indicator (DDFI) system to enhance fuel monitoring accuracy in automobiles using advanced infrared (IR) sensor technology for precise fuel level detection. The innovative system includes a secondary tank, meticulously calibrated to the volumetric ratio of the primary tank, to ensure consistent and accurate readings. The DDFI system provides real-time data on fuel levels with an impressive accuracy of ±5%, a notable improvement over the traditional methods. Key components of the system include an IR sensor, a programmable integrated circuit (IC), and a secondary tank fabricated from galvanized iron (GI) sheet metal, ensuring durability and reliability in various environmental conditions. The system is designed to be user-friendly, offering an intuitive interface for drivers to monitor fuel levels effortlessly. Additionally, the DDFI system integrates seamlessly with existing vehicle systems, allowing for easy installation and minimal
Mallieswaran, K.Nithya, R.Rajendran, ShurutiArulaalan, M.
On-Board-Diagnostics (OBD) are crucial for ensuring the proper functioning of Engine’s emission control system by continuously monitoring various sensors and components. When the failure is detected, the Check Engine Light is triggered on Vehicle’s dashboard, alerting the driver to seek professional service to address the issue. However, the task of developing the monitoring strategies and performing robust calibration is challenging and time consuming. Model in loop (MIL) Simulation and testing is a technique used to understand and estimate the behavior of a system or sub system. The diagnostics model can be tested and refined within the model-based environment allowing a complex system to be efficiently regulated. MIL framework could be explored at various stages of development from early in the design phase to later stages of series developments through vehicle fleet data. This framework allows early identification and correction of errors and bugs in a standalone dependent
Kumar, AmitHegde, KarthikChalla, KrishnaH, YASHWANTH
Calibrated Accelerated Life Testing (CALT) is a sequential and quantitative method for Accelerated Life Testing (ALT). Its design aims to optimize test efficiency by minimizing both test duration and sample size while estimating product life. In the CALT context, the focus is on testing samples under three or more distinct stresses or loads to estimate the life span/BX life, which is a crucial parameter in reliability estimation. Determining the first load in CALT typically involves exploratory testing on a limited number of specimens and relies heavily on engineering judgments such as analyzing Finite Element Analysis (FEA) outcomes, referencing test data from comparable designs and materials, and considering stiffness results etc. This often leads to challenges in accurately identifying the first load/stress. To address this issue, we propose a systematic step-stress test approach instead of exploratory testing. This approach aims to efficiently identify the first load in CALT. The
Patidar, NitinSoma, Nagaraju
The electric vehicle (EV) industry is seeing a significant increase in global investments. However, it faces major challenges, especially the shortage and rising costs of key raw materials needed for battery production. This situation creates higher economic risks for investors. This paper evaluates the risks of investing in the EV industry, considering current supply chain issues related to finding raw materials, manufacturing, and selling. The evaluation uses the beta coefficient, which measures how much an individual stock’s price is expected to fluctuate compared to the overall stock market. To examine the beta coefficient’s variability, a Monte Carlo simulation is used to calculate its changes, providing insights into the volatility of assets in the EV industry relative to market conditions. The simulation is repeated multiple times until consistent results are obtained. The main goal of this study is to offer a forward-looking tool to help with investment decisions in the
Gutierrez, MarcosTaco, Diana
Sensor calibration plays an important role in determining overall navigation accuracy of an autonomous vehicle (AV). Calibrating the AV’s perception sensors, typically, involves placing a prominent object in a region visible to the sensors and then taking measurements to further analyses. The analysis involves developing a mathematical model that relates the AV’s perception sensors using the measurements taken of the prominent object. The calibration process has multiple steps that require high precision, which tend to be tedious and time-consuming. Worse, calibration has to be repeated to determine new extrinsic parameters whenever either one of the sensors move. Extrinsic calibration approaches for LiDAR and camera depend on objects or landmarks with distinct features, like hard edges or large planar faces that are easy to identify in measurements. The current work proposes a method for extrinsically calibrating a LiDAR and a forward-facing monocular camera using 3D and 2D bounding
Omwansa, MarkSharma, SachinMeyer, RichardBrown, Nicholas
Researchers at the National Institute of Standards and Technology (NIST) and colleagues have developed standards and calibrations for optical microscopes that allow quantum dots to be aligned with the center of a photonic component to within an error of 10 to 20 nanometers (about one-thousandth the thickness of a sheet of paper). Such alignment is critical for chip-scale devices that employ the radiation emitted by quantum dots to store and transmit quantum information.
The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation. The ECU is operated on
Meli, MatteoWang, ZezhouBailly, PeterPischinger, Stefan
Society is moving towards climate neutrality where hydrogen fuelled combustion engines (H2 ICE) could be considered a main technology. These engines run on hydrogen (H2) so carbon-based emission are only present at a very low level from the lube oil. The most important pollutants NO and NO2 are caused by the exhaust aftertreatment system as well as CO2 coming from the ambient air. For standard measurement technologies these low levels of CO2 are hard to detect due to the high-water content. Normal levels of CO2 are between 400-500 ppm which is very close or even below the detection limit of commonly used non-dispersive-infrared-detectors (NDIR). As well the high-water content is very challenging for NOx measuring devices, like chemiluminescence detectors (CLD), where it results in higher noise and therefore a worse detection limit. Even for Fourier-transformed-infrared-spectroscopy-analysers (FT-IR) it is challenging to deal with water content over 15% without increased noise. The goal
Jakubec, PhilippRoiser, Sebastian
Severe problem of aerodynamic heating and drag force are inherent with any hypersonic space vehicle like space shuttle, missiles etc. For proper design of vehicle, the drag force measurement become very crucial. Ground based test facilities are employed for these estimates along with any suitable force balance as well as sensors. There are many sensors (Accelerometer, Strain gauge and Piezofilm) reported in the literature that is used for evaluating the actual aerodynamic forces over test model in high speed flow. As per previous study, the piezofilm also become an alternative sensor over the strain gauges due to its simple instrumentation. For current investigation, the piezofilm and strain gauge sensors have mounted on same stress force balance to evaluate the response time as well as accuracy of predicted force at the same instant. However, these force balance need to be calibrated for inverse prediction of the force from recorded responses. A reliable multi point calibration
Kamal, AbhishekDeka, SushmitaSahoo, NiranjanKulkarni, Vinayak
This Aerospace Information Report (AIR) is intended to provide information relating to the construction, calibration, and usage of parallel plate transmission lines in electromagnetic compatibility susceptibility testing.
AE-4 Electromagnetic Compatibility (EMC) Committee
This SAE Aerospace Recommended Practice (ARP) addresses the general procedure for the best practices for minimizing uncertainty when calibrating thermal conductivity and cold cathode vacuum gauges, which includes the vacuum sensor(s) and accompanying electronics necessary for a pressure measurement to be made. It also includes the best practices for an in-process verification where limitations make it impossible to follow the best practices for minimizing uncertainty. Verifying the accuracy and operation of vacuum gauges is critical to ensure the maintenance of processes while under vacuum.
AMS B Finishes Processes and Fluids Committee
This document presents a study on the design and simulation of a high-lift airfoil intended for usage in multielement setups such as the wings present on open-wheel race cars. With the advancement of open-wheel race car aerodynamics, the design of existing high-lift airfoils has been altered to create a more useful and practical general profile. Adjoint optimization tools in CFD (ANSYS Fluent) were employed to increase the airfoil’s performance beyond existing high-lift profiles (Selig S1223). Improvements of up to 20% with a CL of 2.4 were recorded. To further evaluate performance, the airfoil was made the basis of a full three-dimensional aerodynamics package design for an open-wheel Formula Student car. CFD simulations were carried out on the same and revealed performance characteristics of the airfoil in a more practical application. These CFD simulations were calibrated with experimental values from coast-down testing data with an accuracy of 8%.
Karthikeyan, Prthik NandhanRadhakrishnan, Jayakrishnan
This article presents a strategy for the virtual calibration of a large-scale model representing a self-piercing rivet (SPR) connection. The connection is formed between a stack of three AA6016-T4 aluminum sheets and one SPR. The calibration process involves material characterization, a detailed riveting process simulation, virtual joint unit tests, and the final large-scale model calibration. The virtual tests were simulated by detailed solid element FE models of the joint unit. These detailed models were validated using experimental tests, namely peeling, single-lap joint, and cross-tests. The virtual parameter calibration was compared to the experimental calibration and finally applied to component test simulations. The article contains both experiments and numerical models to characterize the mechanical behavior of the SPR connection under large deformation and failure.
André, VictorCostas, MiguelLangseth, MagnusMorin, David
This study presents the constructed electromechanical model and the analysis of the obtained nonlinear systems. An algorithm for compensating the nonlinear drift of a gyroscope in a microelectromechanical system is proposed. Tests were carried out on a precision rotating base, with the angular velocity changing as per the program. Bench testing the gyroscope confirmed the results, which were also supported by the parameter calibration. The analytical method was further validated through experimental results, and a correction algorithm for the mathematical model was developed based on the test results. After calibration and adjusting the gyroscope’s systematic flaws, the disparity in calculating the precession angle was within 1/100th of an angular second over an interval of approximately 1000 s. Currently, research is underway on the new nonlinear dynamic characteristics of electrostatically controlled microstructures. The results of the integrated navigation system of small satellites
Trung Giap, Vu The
Semi-active suspension system (SASS) could enhance the ride comfort of the vehicle across different operating conditions through adjusting damping characteristics. However, current SASS are often calibrated based on engineering experience when selecting parameters for its controller, which complicates the achievement of optimal performance and leads to a decline in ride comfort for the vehicle being controlled. Linear quadratic constrained optimal control is a crucial tool for enhancing the performance of semi-active suspensions. It considers various performance objectives, such as ride comfort, handling stability, and driving safety. This study presents a control strategy for determining optimal damping force in SASS to enhance driving comfort. First, we analyze the working principle of the SASS and construct a seven-degree-of-freedom model. Next, the damping force optimal control strategy is designed by comprising of the Genetic Algorithm (GA) and the Linear Quadratic Regulator (LQR
Zhao, JianLi, WantingZhu, BingChen, ZhichengDing, ShuweiLi, JunweiHao, WenquanZhang, Yong
Electrification is the future of the automotive industry and with the rapid growth of Battery Electric Vehicle (BEV) market, battery protection becomes more and more crucial. Side pole impact is one of the most challenging safety load cases. Rocker assembly, as the first line of defense, plays a significant role during the event. This paper proposes Cleveland-Cliffs Steel Tube as Reinforcement (C-STARTM) protection as an application for rocker reinforcement. For a component level assessment, three-point bending is used as a testing method to replicate pole impact. The performance is compared with aluminum baseline with respect to peak force and energy absorption. Test and CAE simulations have been performed and a well calibrated CAE model is utilized to predict the robustness of various steel designs using different grades, gauges and geometries. It is shown that C-STARTM [1] protection is a scalable and configurable solution that offers superior performance in terms of peak force and
Yu, MiaoHu, JunZhu, FengNazari, Sobhan T.Elengikal, SajanMakrygiannis, JohnZhang, JimmyWang, Yu-WeiStubleski, DawnLuther, Isaac
During the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement. The proposed pre-processing
Petrone, BorisGiovannardi, EmanueleBrusa, AlessandroCavina, NicolòKitsopanidis, Ioannis
Electrification of vehicles is an important step towards making mobility more sustainable and carbon-free. Hybrid electric vehicles use an electric machine with an on-board energy storage system, in some form to provide additional torque and reduce the power requirement from the internal combustion engine. It is important to control and optimize this power source split between the engine and electric machine to make the best use of the system. This paper showcases an implementation of the Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) with minimization in real-time in the dSPACE MicroAutobox II as the Hybrid Supervisory Controller (HSC). While the concept of A-ECMS has been well established for many years, there are no published papers that present results obtained in a production vehicle suitably modified from conventional to hybrid electric propulsion including real world testing as well as testing on regulatory cycles. This paper details all the supportive algorithms
Capito, VicenteKetineni, PranayRizzoni, GiorgioMidlam-Mohler, Shawn
Design of internal combustion (IC) engine pistons is dependent on accurate prediction of the temperature field in the component. Experimental temperature measurements can be taken but are costly and typically limited to a few select locations. High-fidelity computer simulations can be used to predict the temperature at any number of locations within the model, but the models must be calibrated for the predictions to be accurate. The largest barrier to calibration of piston thermal models is estimating the backside boundary conditions, as there is not much literature available for these boundary conditions. Bayesian model calibration is a common choice for model calibration in literature, but little research is available applying this method to piston thermal models. Neural networks have been shown in literature to be effective for calibration of piston thermal models. In this work, Bayesian model calibration will be compared to two neural network-based calibration methodologies for
Wright, StephenRavikumar, AvinashRedmond, LauraMcMahan, ChrisLawler, BenjaminCastanier, Matthew P.Gingrich, EricTess, Michael
Fracture characterization of automotive metals under simple shear deformation is critical for the calibration of advanced fracture models employed in forming and crash simulations. In-plane shear fracture tests of high ductility materials have proved challenging since the sample edge fails first in uniaxial tension before the fracture limit in shear is reached at the center of the gage region. Although through-thickness machining is undesirable, it appears required to promote higher strains within the shear zone. The present study seeks to adapt existing in-plane shear geometries, which have otherwise been successful for many automotive materials, to have a local shear zone with a reduced thickness. It is demonstrated that a novel shear zone with a pocket resembling a “peanut” can promote shear fracture within the shear zone while reducing the risk for edge fracture. An emphasis was placed upon machinability and surface quality for the design of the pocket in the shear zone. A mild
Pilozo-Hibbit, LucasNarayanan, AdvaithAbedini, ArminButcher, Cliff
Optical Image Stabilization (OIS) is a technology used in cameras and camcorders to reduce blur and shaky images or videos caused by unintentional camera movements. The primary goal of OIS is to counteract motion and maintain the stability of the image being captured, resulting in clearer, sharper, and more stable photos and videos. PhotoModeler, a photogrammetry software, advises users to turn off OIS on their cameras. Since the iPhone 7, OIS has become standard on all iPhones and cannot be deactivated. When calibrating an iPhone camera for photogrammetry, the OIS affects the calibration project's marking residual. In photogrammetry and 3D modeling terminology, "marking residual" typically refers to the difference between the observed image points and the corresponding points predicted by the photogrammetric process and refers to pixels. In other words, it represents the error between the actual image measurements and the values calculated by the photogrammetric algorithm. Because of
Neal, JosephLeipold, TaraPetroskey, Karla
As the automotive industry is coming up with various ADAS solutions, RADAR is playing an important role. There are many parameters concerning RADAR detections to acknowledge. Unsupervised Clustering methods are used for RADAR applications. DBSCAN clustering method which is widely used for RADAR applications. The existing clustering DBSCAN is not aligned very well with its hyperparameters such as epsilon (the radius within which each data point checks the density) and minimum points (minimum data points required within a circle to check for core point) for which a calibration is needed. In this paper, different methods to choose the hyperparameters of DBSCAN are compared and verified with different clustering evaluation criteria. A novel method to select hyperparameters of the DBSCAN algorithm is presented with the paper. For testing the given algorithm, ground truth data is collected, and the results are verified with MATLAB-Simulink.
Payghan, Vaibhav SantoshPrajapati, MiitChauhan, Abhisha
The inherent capacity of electric motors to generate substantial instant torque can lead to significant load reversals in electric vehicle driveshafts under specific road conditions and driving maneuvers, highlighting the need for targeted improvements in driveshaft design, particularly in optimizing joint sizing. This paper presents a systematic approach to investigate the root causes of a catastrophic driveshaft failure that occurred during specific vehicle tests on a road with multiple speed bumps, resulting in numerous high torque reversals. The objective was to enhance system robustness through changes in driveshaft design and the manufacturing process, coupled with a software calibration technique to reduce torque demands under such operating conditions. The process encompassed torque measurements at the vehicle level, failure replication on a test rig, and correlation with simulations. Sensitivity analyses of the manufacturing process preceded the finalization of design and
Singh, Deepak VikramJacob, AbijithPaua, KetanVellandi, VikramanMane, Yogiraj
The automobile industry is going through one of the most challenging times, with increased competition in the market which is enforcing competitive prices of the products along with meeting the stringent emission norms. One such requirement for BS6 phase 2 emission norms is monitoring for partial failure of the component if the tailpipe emissions are higher than the OBD limits. Recently PM (soot) sensor is employed for partial failure monitoring of DPF in diesel passenger cars.. PM sensor detects soot leakage in case of DPF substrate failure. There is a cost factor along with extensive calibration efforts which are needed to ensure sensor works flawlessly. This paper deals with the development of an algorithm with which robust detection of DPF substrate failure is achieved without addition of any sensor in the aftertreatment system. In order to achieve this, a thermodynamic model of DPF substate was created using empirical relations between parameters like exhaust flow rate, exhaust
Jain, Praveer KirtimohanYadav, OmkarChendil, ChellapandiKrishnaraj, PR, SivasubramamanianDaithankar, Parag NarsinhaShanmugam Ramakrishnan, Muthu
Regenerative braking is an effective approach for electric vehicles (EVs) to extend their driving range. To enhance the braking performances and regenerative energy, regenerative braking control strategy based on multi objective optimization is explained in this paper. This technical paper would be focusing on extracting optimum Range with effective brake performances without affecting drivability and performances in different drives modes. An extensive research study on public road driving patterns is done to understand the percentage utilization of brakes at various (low-mid-high) speeds as per the customer driving behavior. Multi-Objective optimization function with three vital factors is defined where output generated power, torque smoothness and current smoothness are selected as optimization objective to improve the driving range, braking comfort, and battery lifetime respectively. Braking regeneration maps are calibrated along with optimized foundation brake hardware’s to get
Kumar, PrabhakarK, RajakumarKrishnan, NandhakumarSuhail, Mohammed Thamjeed
This paper introduces a novel approach to automate PID calibration for closed-loop control systems and the creep control function in an electric vehicle. Through a comprehensive literature survey, it is found that this method is the first of its kind to be applied in the field of automated electric vehicle calibration for Creep function. The proposed approach utilizes a systematic methodology that automatically tunes the PID parameters based on predefined performance criteria, including energy consumption and jerk. To implement this methodology, the ETAS INCA FLOW software, which provides guided calibration methods for in-vehicle testing & calibration, is employed. The calibration process is performed on a real-time electric vehicle platform to validate the effectiveness of the proposed approach. The results of this study showcases the advantages of automated PID calibration for closed-loop control systems and creep control function in small commercial electric vehicle. The proposed
G, AshwinJadhav, Vaibhav V.Warule, Prasad B.
This paper gives insights in the theoretical measurement uncertainty of E-Drive rotor position dependent results, like Id and Iq calculations, done by a modern propulsion power analyzer (PA). The calculation of Id and Iqis fundamental to perform control optimization and application tasks for an E-Drive system. To optimize the E-Drive system application towards e.g., best efficiency, best performance, or improved NVH the importance of the testing toolchain is described: a power analyzer delivering the required results, an automation system, and a Design of Experiment tool to set improved target values. Consequently, inverters applications featuring field-oriented control (FOC) with permanent magnet synchronous machines (PMSM) are updated with a chosen control strategy. For achieving a certain behavior of an E-Drive, different degrees of freedom in the Inverter Control Unit are available; Lookup tables Id and Iq represent two fundamental application labels to be considered. Since the
Platzer, ThomasFechter, MichaelKammerstetter, HeribertKolb, Philipp
Implementation calibration of automotive radar systems plays a fundamental but crucial role to guarantee sensor performance. The commonly used method relies on the environment such as a specific test station for static calibration or a straight metal guardrail for dynamic calibration. In this paper, a sequential method for estimating the radar angle misalignment derived from the Lagrange Multiplier Method in solving an optimization problem is proposed. The sequential method, which requires radar measurements and vehicle speed measurements as input, is more environment-free and can yield a consistent estimation. A simulation study is conducted to validate the consistency and analyze the influence of noise. The result shows that the radar azimuth measurement noise has little influence that the bias could be compensated and the effect of non-gaussianity is negligible. The radar velocity measurement noise bias and vehicle speed measurement noise bias have a linear effect whose coefficient
Pan, SongLu, XinfeiRen, WenpingXue, Dan
This SAE Information Report provides a compendium of terms, definitions, abbreviations, and acronyms to enable common terminology for use in engineering reports, diagnostic tools, and publications related to active safety systems. This information report is a survey of terms related to calibration of active safety systems. The definitions offered are descriptions of inputs, outputs, and processes rather than technical specifications. Definitions for end-of-line procedures are not included.
Active Safety Systems Standards Committee
Particulates are among the most harmful emission components of internal combustion engines (ICE)). Thus, emission limits have been widely introduced, e.g., for light- and heavy-duty vehicles. Although there are still engine applications without particulate limitations, the measurement of particulate mass (PM) and particulate number (PN) emissions is therefore of special interest for the development and operation of ICE. For this purpose, a measurement system for PN consisting of a custom-built sample conditioning and dilution system, and a TSI 3790-A10 [1] condensation particle counter (CPC) as particle number counter (PNC) was designed and built. In this work, we present the conditioning and dilution system, the operational parameters, and results from the particle concentration reduction factor (PCRF) calibration. The sampling system was developed in accordance with the current global technical regulations (GTR15) [2] and consists of a heated sampling probe, up to three dilution
Schurl, SebastianKupper, MartinKrasa, HelmutSchmidt, StephanSturm, StefanHeidinger, Andreas
This research examined CPC calibration error due to the instability of 10 nm particle. Tandem DMA set-up was used to measure the actual particle size. Emery oil particle shrinks by 0.3 nm after classifier. Residence time in the downstream also affects the shrinkage with its rate 0.18 nm per second. In addition, we confirmed 7 nm particle shrinks more, as anticipated on Kelvin equation. Due to this shrinkage, CPC detection efficiency of 10 nm was reduced by 3% approximately.
Kojima, KentaroMurashima, YoshikoSakurai, HiromuOtsuki, YoshinoriKondo, Kenji
This Aerospace Recommended Practice (ARP) describes a standard method and means for measuring or calibrating the "Spectrum Amplitude" output of an impulse generator.
AE-4 Electromagnetic Compatibility (EMC) Committee
Microgrids are a topic of interest in recent years, largely due to their compatibility with the integration of distributed renewable resources, capability for bidirectional power flow, and ability to reconfigure to mitigate the effects of faults. Fault diagnosis algorithms are a foundational technology for microgrids. These algorithms must have two primary capabilities. First, faults must be detectable; it is known when the fault occurs. Second, faults must be isolable; the type and location of detected faults can be determined. However, most fault handling research considering microgrids has focused on the protection algorithm. Protection algorithms seek to quickly extinguish dangerous faults which can damage components. However, these algorithms may not sufficiently capture less severe faults, or provide comprehensive monitoring for the microgrid. This is particularly relevant when considering applications involving fault tolerant control or dynamic grid reconfiguration. Although
Heyer, GabrielD'Arpino, Matilde
A new spatial calibration procedure has been introduced for infrared optical systems developed for cases where camera systems are required to be focused at distances beyond 100 meters. Army Combat Capabilities Development Command Armaments Center, Picatinny Arsenal, NJ All commercially available camera systems have lenses (and internal geometries) that cannot perfectly refract light waves and refocus them onto a two-dimensional (2D) image sensor. This means that all digital images contain elements of distortion and thus are not a true representation of the real world. Expensive high-fidelity lenses may have little measurable distortion, but if sufficient distortion is present, it will adversely affect photogrammetric measurements made from the images produced by these systems. This is true regardless of the type of camera system, whether it be a daylight camera, infrared (IR) camera, or camera sensitive to another part of the electromagnetic spectrum. The most common examples of large
All commercially available camera systems have lenses (and internal geometries) that cannot perfectly refract light waves and refocus them onto a two-dimensional (2D) image sensor. This means that all digital images contain elements of distortion and thus are not a true representation of the real world. Expensive high-fidelity lenses may have little measurable distortion, but if sufficient distortion is present, it will adversely affect photogrammetric measurements made from the images produced by these systems. This is true regardless of the type of camera system, whether it be a daylight camera, infrared (IR) camera, or camera sensitive to another part of the electromagnetic spectrum.
In the last few years, the artificial neural networks have been widely used in the field of engine modeling. Some of the main reasons for this are, their compatibility with the real-time systems, higher accuracy, and flexibility if compared to other data-driven approaches. One of the main difficulties of using this approach is the calibration of the network itself. It is very difficult to find in the literature procedures that guide the user to completely define a network. Typically, the very last steps (like the choice of the number of neurons) must be selected by the user on the base of his sensitivity to the problem. This work proposes an automatic calibration procedure for the artificial neural networks, considering all the main hyper-parameters of the network such as the training algorithms, the activation functions, the number of the neurons, the number of epochs, and the number of hidden layers, for modeling various combustion indexes in a modern internal combustion engine
Brusa, AlessandroShethia, Fenil PanalalMecagni, JacopoCavina, Nicolò
Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size. This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important. The hot flow test results show an
Samuels, CallumHoltzman, RanBenjamin, StephenAleksandrova, SvetlanaWatling, Timothy C.Medina, Humberto
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