Browse Topic: Calibration

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Emerging Trends in Emission Optimization2026-26-0229To be published on 01/16/2026
The exhaust emission control is a vital aspect of automotive development, aimed at ensuring effective control of pollutants such as NOx, CO, and HC. The traditional method of calibrating emission control strategies, that requires extensive vehicle testing with both the fresh and aged catalysts under a variety of operating conditions, is a time-consuming process. The frequent changes in emission legislation creates new challenges for achieving a faster time to market and effective utilization of resources. So, the use of automation and machine learning (ML) in the domain of emission control is the need of the hour to proactively tackle these challenges. This paper attempts to explore emerging trends in emission optimization, such as the automated measurement process and ML/AI based data analysis, that can improve the overall process efficiency in the calibration of emission control strategies. The automated measurement process is achieved using the automation software. The data
Dhayanidhi, Hukumdeen, Balasubramanian, Karthick, A, Akash
Development of an Software Algorithm Based Semi-automated Data Acquisition System for Gasoline Vehicle Calibration on Chassis Dynamometer2026-26-0535To be published on 01/16/2026
Vehicle level testing is one of the crucial part of the calibration development. In this, chassis dynamometer is used to collect the vehicle level data. Different engine and vehicle level parameters are logged at various speed and load points covering the entire engine operational zone. This data acquisition is a repetitive activity and covers over 30-40% of the total testing duration. This phase includes base calibration verification, transient development, and emissions-related calibrations, all of which follow a standardized and repetitive sequence. However, these tasks are predominantly performed manually, leading to potential human error and inefficiencies. This paper presents a novel and comprehensive algorithm developed using INCA FLOW software; the first of its kind for this application. Here, crucial vehicle data acquisition activities are identified, mapped into detailed steps. The algorithm introduces a semi-automated, stepwise process for data acquisition during chassis
Kavekar, Pratap Chandrashekhar, Tyagarajan, Sethuramalingam, Agarwal, Nishant Kumar, Shaikh, Wasim, Karadi, Subramanya
A Novel Wide Range Machine Learning Polynomial Regression Formulation for Enhanced Load Cell Calibration Accuracy2026-26-0567To be published on 01/16/2026
Calibration of measuring instruments is of utmost importance in the field of metrology. It is a mandatory pre-requisite for establishing the fidelity of the measurements as well as to lend confidence. Even more critical is the requirement for the master equipment deployed to calibrate the devices in use. This entails that high accuracy needs to be guaranteed in the calibration process, and that the uncertainty be quantified precisely. The widely used conventional least squares polynomial regression formulation for load cell calibration is based on the non-normalized residual, which is the difference between the measured and master values. The nature of this formulation is such that it imparts more weightage on measured values at higher ranges resulting in good accuracy. However, there is a limitation of this same formulation that results in lesser accurate fit at lower values especially if the instrument is to be used in operation over a wide range including lower ranges of the
S Thipse, Yogesh
Calibration strategy to address abnormal engine noise in cold transient driving condition2026-26-0585To be published on 01/16/2026
Passenger vehicle users often maneuver their cars in diverse and unpredictable driving patterns. The vast and varied terrain of the Indian subcontinent further complicates this scenario, introducing unique challenges due to differences in driving expertise, vehicle usage, and environmental conditions. A specific challenge addressed in this paper arises during cold to ambient engine temperatures and transient driving conditions—a critical phase for engine calibration to ensure optimal drivability and emissions performance. With current calibration practices, an after-burn like abnormal engine noise was observed during certain transient driving patterns in cold to ambient temperature conditions. This paper presents a novel calibration methodology designed to eliminate such abnormal noise. The proposed approach involves a step-by-step transient calibration strategy refinement, making the calibration process more robust and adaptable to any driving behavior. The paper outlines the specific
Suna, Bhagyashree, Tyagarajan, Sethuramalingam, Pise, Chetan, Aishwarya, Amritansh
A method of selectively elevating a Seamless Switch Integrated in Fabric2026-26-0596To be published on 01/16/2026
This research presents the construction and working principle of Selectively Elevated Seamless Fabric Switch technology aimed at advancing automotive interior design through enhanced aesthetics, functionality, and user experience by providing a tactile surface that is available for operation only during the activated, elevated state. Traditional mechanical switches often suffer from issues such as dust and water ingress, accidental activation, and a fragmented visual profile. The proposed system integrates concealed controls sandwiched with a fabric surface, with switches selectively elevated only upon user interaction. The design incorporates conductive fabric layers and electromagnetic actuation to achieve seamless integration with vehicle interiors while maintaining responsive tactile feedback. The input provided for activating the switch can be a signal such as gesture or proximity of the user’s finger. Upon activation the switch is selectively elevated and ready for operation due
Mohunta, Sanjay, Panchal, Girish, Puthran, Shaunak
Thermal Management and Engine Calibration Strategies for Enhanced Passive DPF Regeneration in CEV Stage V CI Engines2026-26-0141To be published on 01/16/2026
Meeting the stringent emissions norms of CEV stage V for medium BMEP engines, CI engines present significant challenges. These stringent norms call for a highly efficient DPF. With the increasing demands for high-performance DPFs, the issue of soot accumulation and cleaning presents significant hurdles for DPF longevity. This paper explores the potential of passive DPF regeneration, which leverages naturally occurring exhaust gas conditions to oxidize accumulated soot, offering a promising approach to minimize fuel penalty and system complexity compared to active regeneration methods. The study investigates engine calibration techniques aimed at enhancing passive regeneration performance, emphasizing the optimization of thermal management strategies to sustain DPF temperatures within the passive regeneration range. Furthermore, the paper aims to expand the applicability of passive regeneration across diverse engine loads common in off-highway applications with effective passive
Saxena, Harshit, Gandhi, Naresh, Lokare, Prasad, Shinde, Prashant, Patil, Ajit, Raut, Ashish
A Novel Approach to Optimal Strain Gauge Placement for Structural Assessment: Integrating Close Looping Configuration with Calibration Techniques2026-26-0551To be published on 01/16/2026
Addressing the challenge of optimal strain gauge placement on complex structural joints and pipes, this research introduces a novel methodology combining strategic gauge configurations with numerical optimization techniques. Traditional methods often struggle to accurately capture combined loading states and real-world complexities, leading to measurement errors and flawed structural assessments. For intricate joints, a looping strain gauge configuration is proposed to comprehensively capture both bending and torsional effects, preventing the bypassing of applied loads. A calibration technique is used to create strain distribution matrices and access structural behavior under different loading conditions. Optimization algorithms are then applied to identify gauge placements that yield well-conditioned matrices, minimizing measurement errors and enhancing data reliability. This approach offers a cost-effective solution by reducing the number of gauges required for accurate stress
shingate, Uttam, Yadav, Dnyaneshwar
PSF-Net: Uncertainty-Aware Fusion of TabPFN and SAINT for 5G Base-Station Electromagnetic Radiation Prediction2025-99-012711/11/2025
With more 5G base stations coming into play, making an accurate assessment of RF-EMF exposure currently faces increasing demand to check if they meet regulatory requirements and ensure people’s safety. We present here PSF-Net, a novel deep learning network by uniting TabPFN’s meta-learned prior knowledge and SAINT’s dual attention structure; its use makes it particularly suitable to deal with applications like prediction of downlink power density and radiation level classification under different conditions within various kinds of 5G cell. A major component in the design of this approach is an uncertainty-aware gating block that determines the optimal weighting for each model output—TabPFN or SAINT—based on the estimated prediction variance as quantified via Monte Carlo sampling during training or the prediction variance calculated using inference-time dropout. In addition, a residual multi-layer perceptron (MLP) is also included to extract refined fused features and maintain a steady
Zhang, Yanjin, Yu, Zefeng
A Load Cell-Free Solution for Weighing2025-28-034611/06/2025
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical
Kadam, Pankaj
Advanced Compliance Risk Assessment Using Big Data from Fleet Intelligence Data2025-28-034311/06/2025
In-Use emission compliance regulations globally mandate that machines meet emission standards in the field, beyond dyno certification. For engine manufacturers, understanding emission compliance risks early is crucial for technology selection, calibration strategies, and validation routines. This study focuses on developing analytical and statistical methods for emission compliance risk assessment using Fleet Intelligence Data, which includes high-frequency telematics data from over 500K machines, reporting more than 1000 measures at 1Hz frequency. Traditional analytical methods are inadequate for handling such big data, necessitating advanced methods. We developed data pipelines to query measures from the Enterprise Data Lake (A Structured Data storage system), address big data challenges, and ensure data quality. Regulatory requirements were translated into software logic and applied to pre-processed data for emission compliance assessment. The resulting reports provide actionable
Arya, Satya Prakash, Shekarappa, Kiran
Development of an Artificial Calibrator for Shift Program Optimization to Enhance Fuel Efficiency2025-32-008211/03/2025
The calibration of automotive electronic control units is a critical and resource-intensive task in modern powertrain development. Optimizing parameters such as transmission shift schedules for minimum fuel consumption traditionally requires extensive prototype testing by expert calibrators. This process is costly, time-consuming, and subject to variability in environmental conditions and human judgment. In this paper, an artificial calibrator is introduced – a software agent that autonomously tunes transmission shift maps using reinforcement learning (RL) in a Software-in-the-Loop (SiL) simulation environment. The RL-based calibrator explores shift schedule parameters and learns from fuel consumption feedback, thereby achieving objective and reproducible optimizations within the controlled SiL environment. Applied to a 7-speed dual-clutch transmission (DCT) model of a Mild Hybrid Electric Vehicle (MHEV), the approach yielded significant fuel efficiency improvements. In a case study on
Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman
Automated Calibration of Heavy-Duty Low NO x Aftertreatment System Controls using Deep Learning and Global Optimization Methods2025-01-040210/07/2025
Heavy duty diesel engines provide a robust power plant for transportation applications for both on highway and off road applications. Control of criteria pollutants such as particulate matter and NOx at tailpipe for these applications based on standards set by regulatory bodies such CARB and EPA is critical. SwRI has demonstrated capability to achieve 0.02 g/bhp-hr. tailpipe NOx standard through the application of a model based controls in EPA and CARB funded projects. This control mechanism enables precise urea dosing for both steady state and transient conditions by leveraging estimated ammonia storage state in a dual dosing system using a set of chemical kinetics-based SCR observer models. This controller is highly nonlinear, with a significant amount of controller tuning with up to 55 calibratable parameters. In order to improve the accuracy and reduce the time required for calibration of this controller, this work proposes the deployment of a Deep Learning-based SCR plant model in
Chundru, Venkata Rajesh, Rajakumar Deshpande, Shreshta, Sharp, Christopher, Gankov, Stanislav
Multi-Objective Optimization of the Energy Management Strategy for Hybrid Electric Vehicles -Examination of Sensitivities between Fuel Consumption, Electric Driving and Driving Comfort2025-24-010309/07/2025
The combination of the electric drive and the internal combustion engine (ICE) in hybrid electric vehicles (HEV) requires the implementation of an Energy Management Strategy (EMS). The task of the EMS is to split the driving demand between the two energy converters. The design of the EMS in charge-sustaining operation is commonly targeted at the minimization of fuel consumption. For in-vehicle implementation of the EMS, supplementary objectives, such as the electric driving (ED) experience or the driving comfort, influenced by the frequency of state shifts, are considered. Therefore, this work extends the framework for EMS optimization from the fuel-optimal design to multi-objective target spaces. First, the general multi-objective optimal control problem (MOOCP) is formulated. In a next step the central target space for EMS calibration consisting of fuel consumption, ED time and number of ICE starts is considered and the resulting MOOCP is solved using Dynamic Programming (DP). The
Ehrenberg, Bastian, Engbroks, Lukas, Schmiedler, Stefan, Geringer, Bernhard, Hofmann, Peter
Design of a Fault-Tolerant Control Algorithm for Four-Wheel Steering Vehicle Steering Locking Based on Dynamic Model Reconstruction10-09-04-003608/21/2025
The motion control system, as the core executive component of the automatic hierarchical framework, directly determines whether autonomous vehicles can reliably and stably follow planned trajectories, making it crucial for driving safety. This article focuses on steering lock faults and proposes a cross-system fault-tolerant control (C-FTC) algorithm based on dynamic model reconstruction. The algorithm uses a classic hierarchical collaborative architecture: the upper-level controller employs an MPC algorithm to solve lateral velocity and yaw rate reference values in real-time, while the lower-level controller, designed based on the reconstructed dynamic model, uses an MPC algorithm to adaptively adjust actuator control quantities. In cases where four-wheel steering vehicles lose steering ability due to locked steering axles, the locked axle’s steering angle is treated as a state variable, and healthy actuator outputs are used as control variables to dynamically reconstruct the vehicle
Hu, Hongyu, Tang, Minghong, Chen, Guoying, Gao, Zhenhai, Wang, Xinyu, Gao, Fei
Reducing Traffic Congestion with Reinforcement Learning-Driven Signal Control Systems2025-01-028307/02/2025
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Kalra, Vikhyat, Tulpule, Punit, Giuliani, Pio Michele
NVH Improvement of Transmission Electric Oil Pump with Uneven Pitch Control2025-01-025206/16/2025
This paper proposes an uneven pitch control for electric oil pumps. For the noise reduction of vane pumps, mechanical arrangements of uneven pitch vain angle are widely used. However, the tooth angle of gear-type pumps should be even mechanically. The proposed uneven pitch control provides similar effects of the mechanical uneven pitch arrangement by instantaneous motor torque controls of the electric oil pump which cannot have uneven pitch mechanically. The magnitude of motor torque for each pump tooth is determined by an uneven pitch formula which is widely used for mechanical vane pumps in previous study and patents. A formula for the shape of motor torque is proposed by analyzing pressure fluctuations of pump as a combination of trigonometric and exponential functions. The calibration factors for the magnitude and shape are adjusted by characteristics of pumps. The experimental results showed that noise reduction and dispersion effects of the proposed method.
Choi, Chinchul, Kim, Jongbeom
Development of Offline Simulation Software for Active Sound Design in Electric Vehicles2025-01-001705/05/2025
With the increasing adoption of electric vehicles (EVs), Active Sound Design (ASD) has become a crucial method for enhancing both sound quality and the overall driving experience, addressing the absence of the distinctive engine sounds found in internal combustion vehicles. This paper presents an ASD offline simulation software developed on the MATLAB platform. The software integrates a vehicle dynamics model with three key sound synthesis algorithms—order synthesis, pitch shifting, and granular synthesis—enabling comprehensive control strategy development, real-time sound playback, and rapid adjustments. It comprises multiple functional modules, including configuration, order generation, pitch shifting, and granular synthesis interfaces, offering a user-friendly environment for flexible sound parameter tuning under various simulated driving conditions. Users can easily configure vehicle dynamics, adjust gain values, and visually manipulate sound parameters to create a customized ASD
Qian, Yushu, Xie, Liping, Xiong, Chenggang, Liu, Zhien
Design of a Reactive-Style Muffler for a Formula SAE Race Car2025-01-002405/05/2025
The noise generated by high-performance vehicles like Formula SAE (FSAE) race cars, presents a significant challenge in adhering to strict competition noise regulations. In this study two muffler designs were created: muffler design 1 and 2. Each design utilized two chambers to generate destructive interference, targeting two dominant exhaust frequencies of the Honda CBR600RR engine to maximize transmission loss and reduce sound pressure levels (SPL) below the FSAE-mandated range of 103 dBC at idle and 110 dBC at all other operating conditions. For each design, the exhaust noise and muffler performance were simulated using GT-Suite, allowing for an evaluation of noise attenuation across engine speeds. Experimental testing was conducted to validate the GT-Suite model and assess the effectiveness of muffler design 1. This testing involved measuring the SPL with a calibrated microphone, both with and without the designed muffler. Muffler design 1 was based on the dominant exhaust
Labao, Kai, Middleton, Nicholas, Nuszkowski, John
Novel Statistical Modelling-Based Approach for Exhaust Mass Flow Calculation in Motorcycles2024-32-007204/18/2025
The exhaust mass flow measurement for motorcycles poses a unique challenge due to presence of pulsations arising from an unfavorable combination of the engine displacement-to-exhaust system volume ratio and the long or even unequal ignition intervals. This pulsation phenomenon significantly impacts the accuracy of the differential pressure-based measurement method commonly employed in on-board measurement systems for passenger cars. This paper introduces an alternative approach calculating exhaust mass flow in motorcycles, focusing on statistical modelling based on engine parameters. The problem at hand is rooted in the adverse effects of pulsations on the differential pressure-based measurement method used in the EFM. The unfavorable combination of engine characteristics specific to motorcycles necessitates a novel approach. Our proposed alternative involves utilizing readily available OBD parameters, namely engine speed and calculated engine load as there is mostly no data for intake
Schurl, Sebastian, Sturm, Stefan, Schmidt, Stephan, Kirchberger, Roland
Virtual Calibration Approach to the Development of Control Systems and Strategies for Hybrid L-Category Vehicles2024-32-006604/18/2025
Hybrid powertrain for motorcycles has not been widely adopted to date but has recently shown significant increased interest and it is believed to have great potential for fuel economy containment in real driving conditions. Moreover, this technology is suitable for the expected new legislations, reduced emissions and enables riding in Zero Emissions Zones, so towards a more carbon neutral society while still guaranteeing “motorcycle passion” for the product [1, 2]. Several simulation tools and methods are available for the concept phase of the hybrid system design, allowing definition of the hybrid components and the basic hybrid strategies, but they are not able to properly represent the real on-road behaviour of the hybrid vehicle and its specific control system, making the fine tuning and validation work very difficult. Motorcycle riders are used to expect instant significant torque delivery on their demand, that is not properly represented in legislative cycles (e.g. WMTC); rider
Antoniutti, Christian, Sweet, David, Hounsham, Sandra
CAATS – Automotive Wind Tunnel Calibrations2025-01-876204/01/2025
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, Katlynn, Best, Scott, Nasr Esfahani, Vahid, Senft, Victor, Stevenson, Stuart, Wittmeier, Felix
Evaluation of Several Tesla Dashcam Angles for Model 3 and Y via Reverse Project Photogrammetry2025-01-870004/01/2025
Tesla Model 3 and Model Y vehicles come equipped with a standard dashcam feature with the ability to record video in multiple directions. Front, side, and rear views were readily available via direct USB download. Additional types of front and side views were indirectly available via privacy requests with Tesla. Prior research neither fully explored the four most readily available camera views across multiple vehicles nor field camera calibration techniques particularly useful for future software and hardware changes. Moving GPS instrumented vehicles were captured traveling approximately 7.2 kph to 20.4 kph across the front, side, and rear views available via direct USB download. Reverse project photogrammetry projects and video timing data successfully measured vehicle speeds with an average error of 2.45% across 25 tests. Previously researched front and rear camera calibration parameters were reaffirmed despite software changes, and additional parameters for the side cameras
Jorgensen, Michael, Swinford, Scott, Imada, Kevin, Farhat, Ali
Design of Fault-Tolerant Control Strategy for Dual-Winding Permanent Magnet Synchronous Motor in Vehicles2025-01-880504/01/2025
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, ChaoFan, Zheng, Hongyu, Kaku, Chuyo
Real-time Terrain Analysis for Off-road Autonomous Vehicles2025-01-834304/01/2025
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, Edwina, Parameshwaran, Aditya, Redmond, Laura, Wang, Yue
Reduced Order Model for Viscosity and Mass Density Sensing by A U-Shaped Wire2025-01-847204/01/2025
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, Baoquan, Shen, Yitao, Yang, Jianguo, Zhang, Zhaoying, Wu, Dehong, Zhao, Yingke
Tire Thermal Model with State Observer Integration for Enhanced Real-Time Temperature Prediction2025-01-875604/01/2025
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, Armando, Balaga, Sanjay, labella, Mario, Gorine, Mohamed El Amine
Supervisory Control System Development for a Toyota Mirai FCEV2025-01-858604/01/2025
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 Rajesh, Kubesh, Matthew, Legala, Adithya
Parameter Virtual Calibration Method for Vehicle Path Tracking Controller Based on the Deep Reinforcement Learning2025-01-831104/01/2025
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, Jian, Guo, Chenghao, Zhao, HuiChao, Zhao, Yongqiang, Yu, Zhen, Zhu, Bing, Chen, Zhicheng
Dynamic Evaluation Method for Public Transport Operation Indicators Based on Rank Transformation2025-01-721902/21/2025
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, Yang, Shao, Yichang, Han, Zhongyi, Ye, Zhirui
Vehicle Positioning Technology Based on Stereo Vision2025-01-716302/21/2025
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, Li, Haoping, Qi, Yi, Wei
Modeling Internal Node Impedance in High-Speed Rail Passenger Hubs Based on Queuing Theory2025-01-717202/21/2025
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, Zhenyu, Wang, Jian
Intelligent Vehicle Trajectory Tracking Control Based on Variable Universe Fuzzy Rule Speed Planning and Piecewise Preview Model Prediction02-18-01-000602/06/2025
Intelligent vehicles can utilize a variety of sensors, computing, and control technologies to autonomously perceive the environment and make decisions to achieve safe, efficient, and automated driving. If the speed planning of intelligent vehicles ignores the vehicle dynamics state, it leads to unreasonable planning speed and is not conducive to improving the accuracy of trajectory tracking control. Meanwhile, trajectory tracking usually does not consider the road and speed information beyond the prediction horizon, resulting in poor tracking precision that is not conducive to improving driving comfort. To solve these problems, this study proposes a new longitudinal speed planning method based on variable universe fuzzy rules and designs the piecewise preview model predictive control (PPMPC) to realize the vehicle trajectory tracking. First, the three-degrees-of-freedom vehicle dynamics model and trajectory tracking model are established and verified. Then, the variable universe fuzzy
Zhang, Jie, Teng, Shipeng, Gao, Jianjie, Zhou, Xingxing, Zhou, Junchao
Calibration and Acceptance of Icing Wind TunnelsARP5905A (Current)01/21/2025
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
Model Based Emissions and NVH Optimization2024-36-005912/20/2024
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 Moraes, Santos, Lucas Resende, Nascif, Gabriel Nobre Alves, Oliveira Ribeiro, Douglas, Pereira, Willyan
Design and Implementation of a Detailed Digital Fuel Indicator System for Accurate Fuel Monitoring2024-01-520012/10/2024
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, Shuruti, Arulaalan, M.
Anomaly Detection in Fleet Vehicle Data and Statistical Approach to Develop Engine System OBD Thresholds2024-28-019512/05/2024
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, Amit, Hegde, Karthik, Challa, Krishna, H, YASHWANTH
Calibrated Accelerated Life Testing (CALT) First Load Determination Using Systematic Step Stress Concept2024-28-025112/05/2024
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, Nitin, Soma, Nagaraju
Risk Analysis for Electric Vehicle Investments: Beta Trends and Monte Carlo Insights2024-24-002709/18/2024
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, Marcos, Taco, Diana
Approach for Extrinsic Calibration of a Light Detection and Ranging Sensor and a Monocular Camera Using Bounding Boxes2024-01-509209/04/2024
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, Mark, Sharma, Sachin, Meyer, Richard, Brown, Nicholas
A Method to Accurately Center Quantum Dots Within Photonic ChipsTBMG-5142209/01/2024
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.
Neural Network Modeling of Black Box Controls for Internal Combustion Engine Calibration2024-01-299507/02/2024
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, Matteo, Wang, Zezhou, Bailly, Peter, Pischinger, Stefan
Challenges of Measuring Low Levels of CO 2 and NO x on H 2 -ICE2024-01-299807/02/2024
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, Philipp, Roiser, Sebastian
Experimental Analysis of Force Recovery and Response Time Using Strain Measurement Sensors in Stress Wave Force Balance2024-26-045106/01/2024
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, Abhishek, Deka, Sushmita, Sahoo, Niranjan, Kulkarni, Vinayak
Construction and Calibration of Parallel Plate Transmission Line for Electromagnetic Interference Susceptibility TestingAIR1209 (Current)05/29/2024
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
Vacuum Gauge CalibrationARP7446A (Current)05/17/2024
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
Optimizing High-Lift Airfoils for Formula Student Vehicles2024-01-505905/13/2024
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 Nandhan, Radhakrishnan, Jayakrishnan
A Virtual Calibration Strategy and Its Validation for Large-Scale Models of Multi-Sheet Self-Piercing Rivet Connections05-17-03-001604/29/2024
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, Victor, Costas, Miguel, Langseth, Magnus, Morin, David
Analysis of Error Mechanisms of Vibrating Gyroscopes Operating in a Slowly Changing Environment2024-01-504404/17/2024
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
The Effect of Image Stabilization on PhotoModeler Project Accuracy2024-01-247404/09/2024
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, Joseph, Leipold, Tara, Petroskey, Karla
Benchmarking of Neural Network Methodologies for Piston Thermal Model Calibration2024-01-259804/09/2024
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, Stephen, Ravikumar, Avinash, Redmond, Laura, McMahan, Chris, Lawler, Benjamin, Castanier, Matthew P., Gingrich, Eric, Tess, Michael
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