Browse Topic: Electrical, Electronics, and Avionics

Items (55,416)

Comprehensive Review on Strategies for Preventing and Managing Thermal Runaway in Lithium-Ion Batteries for Electric Vehicles

2025-32-0099To be published on 11/03/2025

The rapid growth of electric vehicle adoption has elevated lithium-ion batteries as a cornerstone of modern transportation. However, this advancement is accompanied by increasing incidents of thermal runaway, a hazardous failure process involving uncontrolled temperature rise, combustion, or explosion. Particularly in space-constrained platforms such as electric two-wheelers, the risk is intensified due to limited thermal buffers and cost-driven design constraints. This study presents a comprehensive review and experimental investigation into strategies for preventing and managing thermal runaway in lithium-ion batteries. It begins by analyzing global incident trends and correlating them with the expanding electric vehicle market. The research examines the fundamental mechanisms of thermal runaway, emphasizing the roles of battery aging, material degradation, internal defects, and abuse conditions. A range of thermal safety enhancement approaches is critically reviewed, including

Jain, Gaurav, PREMLAL, P, Pathak, Rahul, Gore, Pandurang

Methodology of Minimum Energy Starting for SI Engine

2025-32-0090To be published on 11/03/2025

In a general purpose of small SI engine, it is required to reduced fuel consumption under the operating conditions of repeated start and stop. In other words, the energy distribution during starting from 0 rpm to idling speed is an important factor of information. The SI engine needs to be driven by the motor at the starting, and its electrical energy must be minimized. However, the engine itself needs to accelerate during starting, and its electrical energy is affected by compression, friction and moments of inertia. The purpose of this research is to clarify experimentally the starting condition that minimizes this electrical energy. This research has made it possible to divide and measure the frictional and compressional loss and the loss due to the moment of inertia during engine acceleration. Specifically, the effect of the moment of inertia was eliminated by using a motor to keep the engine in a constant state of rotation. This allows the electrical energy used by friction to be

Matsuura, Yusuke, Tanaka, Junya

Measurement of the liquid fuel film on the combustion chamber wall of a gasoline engine using a novel capacitance sensor

2025-32-0018To be published on 11/03/2025

During a cold start and warm-up operation of an SI gasoline engine, a liquid fuel film is formed on the intake port and piston walls. The liquid fuel film attached to the wall increases exhaust unburned HC, particulate matter (PM) emissions, and oil dilution. It is essential to investigate the formation process of the fuel liquid film to reduce exhaust emissions and improve thermal efficiency. Compact fuel film measurement sensors are required for application in the production engine measurement. In this study, a liquid film sensor detecting changes in capacitance due to the liquid film has been developed. The newly developed liquid film sensor was installed and demonstrated into the combustion chamber wall of a single-cylinder gasoline engine. As a result, the liquid film behavior on the combustion chamber wall was successfully detected.

Kuboyama, Tatsuya, Nakajima, Takeru, Moriyoshi, Yasuo, Takayama, Satoshi, Nakabeppu, Osamu

Predicting Transient Soot Emissions in Diesel Engines Using Physical and Machine Learning Models

2025-32-0017To be published on 11/03/2025

In recent years, emissions regulations for engines have been globally strengthened, and many countries, including the United States, have added real-world testing using Portable Emissions Measuring Systems (PEMS) as new test requirements. In the development of diesel engines, improving fuel efficiency and simultaneously reducing NOx and soot emissions are critical challenges, and evaluations using Model-Based Development (MBD) are considered promising methods. However, it is still difficult to accurately predict soot emission, even with detailed combustion models using computationally intensive 3D-CFD, due to the complex mechanisms of soot formation. While various approaches have been researched for prediction methods, they are often limited to specific injection and operating conditions, and an industry-standard model has to be established yet. This paper presents a method for predicting NOx and soot emissions in diesel engines under arbitrary transient test cycles. Fuel consumption

Kitamura, Takahiro, Matsuoka, Ayano, Suematsu, Kosuke, Okano, Hiroaki

Forward-Looking SiL-Based Fuel Consumption Simulation for Dual-Clutch Transmission Software Evaluation

2025-32-0070To be published on 11/03/2025

Evaluating the impact of software changes on fuel consumption and emissions is a critical aspect of transmission development. To evaluate the trade-offs between performance improvements and potential negative effects on efficiency, a forward-looking Software-in-the-Loop (SiL) simulation has been developed. Unlike backward calculations that derive fuel consumption based solely on cycle speed and engine speed, this approach executes complete driving cycles as the Worldwide Harmonized Light-Duty Vehicle Test Cycle (WLTC) within a detailed SiL environment. By considering all relevant influencing factors in a dynamic simulation, the method provides a more accurate assessment of fuel consumption and emission differences between two versions of the transmission software. The significant contribution of this work lies in the high-fidelity integration of a real virtual Transmission Control Unit (vTCU) software within a comprehensive, validated forward-looking SiL environment. This approach

Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman

Study on Combustion Detection of a Spark-Ignition Engine with Fuel Variation Using Various Sensors

2025-32-0052To be published on 11/03/2025

The use of alternative fuels, such as biofuels and synthetic fuels in automotive engines has been more common these days. Although these fuels contribute to the carbon neutral society, it is known that changes in the composition of these fuels significantly affect the combustion characteristics of an engine, such as knocking and combustion duration. Therefore, it is necessary to develop engine systems that are highly robust to variations in fuel composition. To achieve this goal, detecting changes in fuel using various sensors is required. Although in-cylinder piezoelectric pressure sensor is useful for research in the laboratory, it is not suitable for the use in commercial engines because of its high cost. Therefore, the use of other sensors should be considered. The purpose of this study is to experimentally analyze what information related to combustion and fuel can be obtained from multiple cost-effective sensors mounted on an engine. Experiments were conducted on a 4-cylinder SI

HAYASHI, Kohei, KIM PhD, Jihoon, YAMASAKI PhD, Yudai

Knock Sensors for Two Wheelers Applications

2025-32-0079To be published on 11/03/2025

Knock sensors are widely used in automotive engine management applications. It is used for detection of abnormal engine detonation (knocking) and serves to improve combustion performance. It is basically mandatory to comply with regulations for gasoline engines. Pushed by same regulations, and with the implementation of Electronic Fuel Injection (EFI) on two wheelers engines, the door is open to further optimize combustion performance and driving comfort by adding knock sensor. It has large benefit on the ratio of combustion efficiency vs costs. With increased interest of two wheelers OEMs, knock sensors become essential for modern two wheelers applications and set new standards on combustion performances. The sensors are using piezo electric ceramic elements to detect mechanical vibration and transmit the electric signal to the ECU. It has fast analog response and is suitable for high-frequency detection. The wide frequency response allows one common sensor for multiple platforms

van Est, Jeroen, Prieu, Corentin

On Board Monitoring of Water Injection Inducement System and Particulate Filter for 3-Wheeler BS VI OBD II B Diesel Vehicle Norms.

2025-32-0086To be published on 11/03/2025

To mitigate greenhouse emission reduction Government of India implemented Bharat Stage VI (BS-VI) norms from year 2020. Moving to more stringent emission norms poses challenges for automakers in several ways such as meeting exhaust emissions, on board diagnostic, drivers’ inducement, and catalyst monitoring on vehicles. It is imperative to upgrade engine management system for On-board diagnostics (OBD) that refers to a vehicles self-diagnostic and reporting ability. OBD systems enables owner of vehicles to gain access of the various vehicle sub-systems. OBD-II standards were made more rigid, requiring the Malfunction Indicator Lamp (MIL) to be activated if emission-related components fail. Also, vehicle emissions not to exceed OBD thresholds. Consequently, the use of specific NOx emission control systems became necessary in BS VI OBD II B for 3-wheeler applications. Additionally, the performance and integrity of the catalytic converter must be monitored. Driver warnings, inducement

Jagtap, Pranjal, Syed, Kaleemuddin, Chaudhari, Sandip, Khairnar, Girish, Bhoite, Vikram, Reddy, Kameswar

Vehicle to Vehicle Recharge and Power Sharing for Modular Public Transportation Systems: Design and Testing of the UNIFI fleet at ENEA CASACCIA Research Center

2025-32-0095To be published on 11/03/2025

An optimized and capillary diffusion of sustainable public transportation systems often involve the availability of modular and scalable solutions that can be easily adapted to a variable transportation demand in a very fast way or even in real-time. For this reason, there is a growing industrial interest for the development of modular transportation systems composed by relatively small electric units (small modular e-buses with installed battery power of about 15kWh) that should be used to assemble smart intelligent compositions according to transportation demand of customers. University of Florence and Enea Research Center of Roma Casaccia have developed a fleet of electric mini-Buses for the testing of technologies related to this kind of applications (assisted or autonomous drive functionalities, motion, and trajectory controllers, coordinated smart power management etc.). In this work attention is focused on design and testing of the energy management system that assure the

Alessandrini, Adriano, Berzi, Lorenzo, Fabbri, Marco, Franci, Michael, Gulino, Michelangelo Santo, Pugi, Luca, Ortenzi, Fernando, Vitiello, Francesco

Development of CAE Technology for the Design Support of Piston Pin Circlip

2025-32-0015To be published on 11/03/2025

This study focuses on the technology for establishing design criteria for the piston pin circlip (hereinafter referred to as "circlip"), which is a component that holds the engine piston pin. The circlip is assembled into the piston by compressing it to the size of the piston circlip groove. However, in high-revving engines, the inertia forces caused by engine rotation can cause the circlip to disengage from the groove, potentially leading to the piston pin falling out and damaging the engine. To prevent this, it is possible to compress the circlip more and increase the reactive force acting on the groove to prevent falling out. However, this countermeasure raises concerns about the deterioration of the assemblability of the circlip. Therefore, it is necessary to establish evaluation criteria that prevent the circlip from disengaging and deteriorationg the assemblability of the circlip. To enable appropriate design of the circlip during the engine specifications review phase, we

Ishizuka, Atsushi, Watanabe, Naoto

Analysis of injected mass shot-to-shot dispersion and injection rate profile for a PFI injector in actual operating conditions

2025-32-0019To be published on 11/03/2025

In order to improve engine emission and limit combustion instabilities, in particular for low load and idle conditions, reducing the injected fuel mass shot-to-shot dispersion is mandatory. Unfortunately, the most diffused approach for the hydraulic analysis of low-pressure injectors such as PFIs or SC R dozers is restrained to the mean injected mass measurement, since the use of conventional injection analysers is unfeasible. In the present paper, an innovative injection analyser is used to measure the injection rate and the injected mass of each single injection event, enabling a proper dispersion investigation of the studied system. The proposed instrument is an inverse application of the Zeuch’s method, which in this case is applied to a closed volume upstream the injector, with the injector being operated with the prescribed upstream-downstream pressure differential. Further, the injector can inject freely against air, thus enabling simultaneous analyses of the resulting spray

Postrioti, Lucio, Maka, Cristian, Martino, Manuel

Machine Learning-Enhanced Electrical Circuit Model Parametrization for Battery Cells: Reducing Experimental Workload Through GITT Testing with Altair RapidMiner®

2025-32-0097To be published on 11/03/2025

This study addresses the challenge of reducing the experimental workload involved in characterizing battery cell behavior as a function of state of charge and temperature. Galvanostatic Intermittent Titration Technique tests were carried out in a climate chamber across a wide temperature range, from -20 °C to 70 °C, with 10 °C intervals. The voltage and current response data collected from these tests were used to train several machine learning algorithms. The trained models could then be used to predict the cell voltage response every 5 °C from -15 °C to 55 °C. While the models were experimentally validated at 15 °C, 25 °C, and 35 °C, the predicted voltages across this range contribute to enhancing the characterization process. In particular, the inclusion of these predicted voltage profiles—combined with the experimental data collected every 10 °C from -20 °C to 70 °C—allows for the creation of more accurate lookup tables for the parameters of the equivalent circuit model. These

Giuliano, Luca, Peretto, Lorenzo, Canella, Nicholas, Nefat, Damir

An SVM-based approach to develop a new control module for H2-powered engine using driver behaviour classification

2025-32-0042To be published on 11/03/2025

In the next years, the global hydrogen vehicle market is expected to grow at a very high rate. Consequently, it is necessary for scholars and professionals to study and test specific components in order to rise motor efficiency leveraging the new features of connectivity available in smart roads. In particular, our research is focused on the developement of an engine control module driven by evaluation of usage characteristics (e.g., driving style) and "connected-to-x" scenarios using the standard engine control approach. Moreover, the module proposed enables the implementation of "fast running" models to improve the response of vehicle and make the best possible use of H2-powered engine characteristics. That said, in this paper is proposed a new approach to implement the control module, using Support Vector Machine (SVM) as the machine learning algorithm to detect driving style, and consequently modify the parameters of the engine. We choose SVM because i) it is less prone to

Mastroianni, Michele, Merola, Simona, Irimescu, Adrian, De Santis, Marco, Esposito, Christian, Aversano, Lerina

Development of the Anti-SideSlip Control for Motorcycles Using IMU

2025-32-0037To be published on 11/03/2025

Motorcycles typically turn by generating camber thrust by leaning the body. However, in Competitions that emphasize speed like races, there is a technique to intentionally make the rear wheel slide laterally to reduce the turning radius, allowing for faster turns than using only camber thrust. While this technique is effective for faster riding, it is difficult to execute and carries risks such as falling. Therefore, the aim was to develop a control system that detects lateral sliding and controls the amount of slide, enabling natural and highly stable cornering. However, detecting lateral sliding in motorcycles presents challenges, particularly in detecting the slip angle. While electronic stability control (ESC) for preventing lateral sliding is already practical in four-wheeled vehicles, motorcycles differ as they turn by leaning the body, making it impossible to detect the slip angle using steering angle and yaw rate. To determine the slip angle in motorcycles, optical sensors like

Nakano, Kyosuke, Kawai, Kazunori, Takeuchi, Michinori

Investigating the Influence of Intake Runner Configuration on Scavenging and Combustion Processes in Elliptical Rotor Engines

2025-32-0089To be published on 11/03/2025

Elliptical rotor engines (ERE), also known as X-engines, feature intake and exhaust ports located on the rotating rotor. As the rotor turns, these ports traverse the entire combustion chamber, sequentially completing the scavenging process in three distinct combustion chambers through coordination with the cylinder walls. This intake and exhaust characteristic significantly differs from the characteristic found in traditional Wankel rotor engines. This study established an optical elliptical rotor engine to obtain the in-cylinder flow field by using Particle Image Velocimetry (PIV) and constructed a CFD model based on the experimental results. Then the effects of two different intake runners on the scavenging and combustion process of ERE were investigated. The results indicated that: Due to structural limitations, the prolonged intake port opening duration results in significant gas backflow during the intake process. The curved intake runner exhibits a higher turbulent kinetic energy

Qin, Jing, Wang, Yingbo, Pei, Yiqiang, Yao, Dasuo, Deng, Xiwen

Safety Critical Series Arc Detection and Measurement in Medium and High Voltage DC Grids

2025-32-0012To be published on 11/03/2025

Direct current (DC) systems are increasingly used in small power system applications ranging from combined heat and power plants aided with photovoltaic (PV) installations to powertrains of small electric vehicles. A critical safety issue in these systems is the occurrence of series arc faults, which can lead to fires due to high temperatures. This paper presents a model-based method for detecting such faults in medium- and high-voltage DC circuits. Unlike traditional approaches that rely on high-frequency signal analysis, the proposed method uses a physical circuit model and a high-gain observer to estimate deviations from nominal operation. The detection criterion is based on the variance of a disturbance estimate, allowing fast and reliable fault identification. Experimental validation is conducted using a PV system with an arc generator to simulate faults. The results demonstrate the effectiveness of the method in distinguishing fault events from normal operating variations. The

Winkler, Alexander, Mayr, Stefan, Grabmair, Gernot

Strategies for Improving Energy Consumption for Electric Vehicles.

2025-32-0092To be published on 11/03/2025

The global transition toward sustainability and decarburization has positioned Electric Vehicles (EVs) at the forefront of future mobility. While EVs inherently offer lower emissions compared to internal combustion engine (ICE) vehicles, optimizing their energy efficiency remains a critical challenge to ensure their viability, affordability, and widespread adoption. With global EV sales surpassing 10 million units in 2022 representing over 14% of the global vehicle market. Energy efficiency has emerged as a cornerstone in addressing key concerns such as range anxiety, charging infrastructure, operational costs and overall environmental impact. This paper embarks on a comprehensive journey, beginning with the historical evolution of EVs and identifying the multifaceted energy losses that occur during vehicle operation. By mapping the energy distribution within a typical EV, the study lays a foundational understanding of where and how inefficiencies arise. It then explores current

Jain, Gaurav, PREMLAL, P, Pathak, Rahul, Gore, Pandurang

Static Wheel Alignment Predictive Model of Electric Sports Utility Vehicle

2025-32-0032To be published on 11/03/2025

This paper introduces a data-driven approach to wheel alignment prediction with machine learning models (XGBoost and Random Forest) trained on eleven critical vehicle parameters like weight distribution, dimensional specification, tire specification, and suspension geometry. The research emphasizes finding predictive correlations between vehicle specifications and ideal alignment settings and presents complete framework as single objective function with tire wear minimization, rolling resistance reduction, and target understeer preservation which allows alignment optimization without violating physical constraints. The prediction models obtain accuracy with MAE value of 0.03 and variance score of 0.85 through the modeling of intricate nonlinear interactions between vehicle specification and past alignment settings. The overall accuracy of the XGBoost model predicted value is 75% with respect to the final vehicle specification of the production vehicle. The optimization framework

Kumar, Avinash, Rasal, Shraddhesh, Asthana, Shivam, Thakur, Pragyesh, M, Sudhan

Analysis of Flame Propagation Characteristics in a Hydrogen Engine using an Optically Accessible Engine

2025-32-0061To be published on 11/03/2025

In recent years, the progress of global warming and the response to environmental problems have become important global issues, and efforts are being made to achieve carbon neutrality. In this context, the automotive and energy industries, which are required to reduce carbon dioxide emissions, have an urgent need to move away from fossil fuels. Especially in small engines, efficiency and cleanliness are important themes, and the introduction of hydrogen fuel is attracting attention as one solution to this. Hydrogen does not emit carbon dioxide when combustion and is considered to be a clean energy source, but due to the difference in characteristics from hydrocarbon fuels used in the past, there are still many unclear points about its combustion behavior and application to engines, and this information is indispensable for improving the performance and efficient operation of hydrogen engines. Therefore, in this study, we investigated the effect of hydrogen on flame propagation and

Arai, Yuto, Ueno, Takamori, Suda, Ryosuke, Sato, Ryoichi, Nakao, Yoshinori, Ninomiya, Yoshinari, Matsushita, Koichiro, Kamio, Tomohiko, Iijima, Akira

Road Simulation Techniques for Reproducing Off-Road Vehicle Behavior

2025-32-0031To be published on 11/03/2025

A road simulator reproduction method was developed to reproduce the off-road conditions of utility vehicles in a laboratory setting. Off-road running behavior can be reproduced by considering the effects of inertial forces from jump landings owing to uneven terrain and slow-speed navigation. However, extremely low-frequency components and behaviors, including inertial forces from jumps, vehicle acceleration and deceleration, are difficult to reproduce with a normal road simulator in the limited test space of a laboratory. Therefore, it is common practice to intentionally remove input components below 1 Hz. Alternatively, inertial forces can be reproduced by adding a restraining device to the sprung mass of the vehicle along the wheel-axle inputs. Therefore, the former method excludes extremely low- frequency components, whereas the effects between actuators, which increase the test complexity and time required, should be canceled in latter method. Furthermore, the restraining device on

Miyasaka, Takahiro, Shimizu, Ryota

Development of a Fuel Cell System for Small Mobility Applications with Severe Load Fluctuations

2025-32-0038To be published on 11/03/2025

In recent years, small electric mobility powered by fuel cells have been proposed as a way to achieve a carbon neutral society. One reason for the proposal is that fuel cells have an advantage over battery electric vehicle (BEV) in traveling range and refueling time. This study develops a hybrid system combining a fuel cell and a lithium-ion capacitor (LiC) for small electric mobility applications with severe load fluctuations. The proposed system achieves a 53% reduction in size, a 50% reduction in weight, and a 23% improvement in acceleration performance compared to a configuration using a lithium-ion battery (LiB) as the secondary battery, while also reducing load fluctuations in the fuel cell. Although LiCs tend to be compact, lightweight, and capable of high output, they have limited discharge capacity. To address this, a prototype hybrid system combining a fuel cell and an LiB was initially constructed to verify the system’s ability to suppress load fluctuations through current

suzuki, masaya, Nakata, Nobuhiro

Transient Helium Jet Evolution Using High Speed Schlieren Imaging

2025-32-0057To be published on 11/03/2025

The accelerating global shift towards decarbonised energy systems has positioned hydrogen as a highly promising carbon-free fuel. This study comprehensively investigates the macroscopic characteristics and temporal evolution of vortex ring trailing helium jets, serving as a surrogate for hydrogen, injected into a quiescent ambient environment using high-speed Schlieren imaging. This research addresses critical insights into fuel-air mixing dynamics essential for optimising hydrogen direct injection (DI) internal combustion engines. Analysis of helium jet tip’s topology revealed a three-stage evolution from an initial pressure-insensitive phase, dominated by pressure wave structures, to a momentum-driven, vortex-dependent growth stage, then to a fully developed stage. Specifically, the lower-pressure cases showed increased Kelvin-Helmholtz instability and distinct head vortex pinch-off at the final stage. Jet tip velocities transitioned from initial high, rapid pressure wave development

Dong, Shuo, Shi, Hao, Zhang, Gengxin, Feng, Yizhuo, Lu, Enshen, Wang, Xinyan, Zhao, Hua

Development of an Artificial Calibrator for Shift Program Optimization to Enhance Fuel Efficiency

2025-32-0082To be published on 11/03/2025

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, we introduce an artificial calibrator – 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 1.5 L Mild Hybrid Electric Vehicle (MHEV), the approach yielded significant fuel efficiency improvements. In a case

Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman

Development of Electronic Control in Strong Hybrid Motorcycle

2025-32-0091To be published on 11/03/2025

In response to the growing demand for environmental performance, the mobility industry is actively developing electrification, and in particular, the use of Battery Electric Vehicles (BEV) in commuting motorcycles is advancing. However, in the case of vehicles for leisure, which require high riding performance, there are problems such as cruising range and charging time, and there are currently few mass-produced models. Therefore, we proposed a hybrid motorcycle to achieve both environmental performance and high riding performance by means other than BEV. The proposed vehicle is equipped with a strong type hybrid system in which an engine and a drive motor are connected in parallel via a hydraulic electronically controlled clutch. It is possible to run only by the motor (EV driving) or by a hybrid running powered by both the engine and the motor (HEV driving). In order to improve environmental performance, it is necessary to develop a function for switching between EV and HEV driving

Obayashi, Kosuke, Terai, Shohei, Jino, Kenichi, Kawai, Daisuke

Electrification potential of Small ICE Powertrain Applications

2025-32-0094To be published on 11/03/2025

The reduction of the CO2 footprint of transport vehicles is a major challenge to minimize the harmful impact of technology on the environment. Besides passenger cars and light and heavy-duty vehicles, this affects also the two-wheeler category and the non-road mobile machinery (NRMM). One promising path for the de-carbonisation is the transition from fossil-fuel powered ICE powertrains to electric powertrains. Several examples of electrified powertrains showcase possibilities for small hand-held powertools or small mopeds and scooters. As the powertrain categories two-wheeler and NRMM are very diversified and consist of various sub-categories and sub-classes with many different applications, the feasibility of electrification for the whole category cannot be judged by few examples. In this publication a methodology for assessing the electrification potential of small NRMM and two-wheelers is shown. The method uses 4 different factors, which determine the feasibility for electrification

Schmidt, Stephan, Schacht, Hans-Juergen, Weller, Konstantin, Absenger, Johann Friedrich

Investigation of Transient High Current Ignition for Lean Mixture in Spark Assisted Compression Ignition

2025-01-0390To be published on 10/07/2025

Lean burn combustion is an effective strategy to reduce the in-cylinder temperature, hence reduce NOx emission and increase the thermal efficiency of the system. One essential aspect of successful combustion is the flame kernel initiation and development. However, as the fuel-air mixture becomes leaner, challenges arise in achieving a stable flame kernel initiation. This empirical research aims to investigate the impact of the transient high current strategy on early flame initiation in lean mixtures of Dimethyl Ether (DME). Additionally, with the onset of auto-ignition, the impact has been further investigated for the overall combustion period. In this work, a rapid compression machine is utilized to create an engine-relevant conditions, pressure of 16.4 bar and temperature of ~620K, with DME as a volatile and highly reactive fuel. Prior to auto-ignition, spark-assistance is applied to enable a spark-assisted compression ignition mode. The spark event is initiated by a transient high

Asma, Sabrina, Yu, Xiao, Jin, Long, Tjong, Jimi, Zheng, Ming

Development of a virtual test rig to evaluate thermal management of a battery-electric vehicle under a heating-cooling mode

2025-01-0413To be published on 10/07/2025

This work presents a systematic approach to developing a virtual test rig for evaluating the thermal performance of battery electric vehicles. A mass-produced battery-electric sport utility vehicle is tested in a chassis dynamometer, and the measured vehicle performance data are used as boundary conditions for the complete vehicle model. The detailed lithium-ion battery (LIB) pack model with its cooling system was developed and calibrated with various transient driving cycle data. The HVAC model is developed using a simplified controller to maintain the cabin temperature at 25 °C during both heating and cooling modes. The complete vehicle model is used to compare the thermal performances of the BEV under cabin heating and cooling modes for various transient driving cycles. The simulated results show that using an external cabin air circulation model can reduce the battery energy consumption and dissipated heat by 9.9% and 2.4%, respectively.

Sok, Ratnak, Kusaka, Jin

Development of a Self-Adjusting Engine Out NOx Prediction Model Using Tailpipe O2 Measurements

2025-01-0381To be published on 10/07/2025

On-Board Diagnostic (OBD) strategies utilize a predictive model to estimate engine out NOx levels for a given set of operating conditions to ensure the accuracy of the Nitrogen Oxides (NOx) sensor. Furthermore, this model is also used to determine urea dosing quantities in situations where the NOx sensor is unavailable such as cold starts or as a reaction to a NOx sensor plausibility failure. Physics-based NOx prediction models guarantee high levels of accuracy in real-time but are computationally expensive and require measurements generally not available on commercial powertrains making them difficult to implement on controllers. Consequently, manufacturers tend to adopt a mathematical approach by estimating NOx under standard operating conditions and use a variety of correction factors to account for any changes that can influence NOx production. Such correction factors tend to be outcomes of base engine calibration settings or outputs of models of other related sub systems and may

Sunder, Abinav, Suresh, Rahul, Polisetty, Srinivas

Optimal Control Strategy for BEV with CVT Using Dynamic Programming Method

2025-01-0407To be published on 10/07/2025

Optimal Control Strategy for BEV with CVT Using Dynamic Programming Method Authors: Hanqing Zhao, Yasuo Moriyoshi, Tatsuya Kuboyama Abstract Battery electric vehicles (BEVs) equipped with high-speed, low-torque motors can benefit greatly from the use of continuously variable transmissions (CVTs). This study aims to reduce energy consumption by adjusting the CVT ratio to ensure that the motor operates in its optimal efficiency range during both traction and regenerative braking, while delivering the required power with minimal power loss. A detailed mathematical model of a dual motor, single CVT EV powertrain and transmission structure was developed to establish an optimal control problem aimed at minimizing energy consumption. Three methods were compared to evaluate their effectiveness: (1) The basic simulation method, which directly uses the existing control map to control the CVT ratio based on torque, vehicle speed, and motor speed; (2) The steady-state method, which searches all

ZHAO, HANQING, Moriyoshi, Yasuo, Kuboyama, Tatsuya

Application of Machine Learning to Engine Fuel System Failure Prediction

2025-01-0377To be published on 10/07/2025

The automotive industry prioritizes reliability and minimizes downtime, leading to a rapid embrace of predictive maintenance to curtail unforeseen failures and associated expenses. Traditional reactive maintenance strategies often prove inadequate in accurately forecasting failures, resulting in costly operational disruptions. This paper introduces a novel machine learning-driven method for predicting engine fuel system failures using anomaly detection algorithms applied to telematics data. By analyzing intricate relationships between fuel system components and operational features, our approach aims to enhance vehicle reliability and reduce maintenance costs. We present a comprehensive methodology encompassing data acquisition, data preprocessing, and feature engineering, leveraging key features such as rail pressure deviation, fuel pump metering valve current, engine torque, and engine speed to establish a benchmark for healthy vehicle operation, all sampled at one-minute intervals

WANG, TINGTING, goswami, Anil, Akinola, Michael, YANG, TINA, An, Qi

Passive solution for Battery Disconnect Unit thermal management for electric vehicle fast charging: numerical study and experimental validation

2025-01-0420To be published on 10/07/2025

Charging time is a major problem with electric vehicles development and use. The difficulty of finding a charging station and especially the duration needed for a full charge are becoming more and more important topics in electric vehicles selling points. Fast-charging is more and more used on new developed vehicles but also on existing vehicles. One of the limits of fast-charging electric vehicles is the overheating of the different components in the car, the station, and the charging system. One of the key components in this system is the battery disconnect unit. This element is responsible for monitoring, activating and deactivating the high voltage battery system. It is essential to maintain it at convenient temperatures and prevent it from overheating. These components are designed today for normal charging power, but with increasing charging powers and reducing charging time, thermal management of these components become essential. This paper presents a passive way to allow the

Salameh, Georges, Goumy, Guillaume, Chalet, David, Dubouil, Rémi, Frecinaux, Anthony, Palluel, Marlène, Ratajczack, Christelle, Noiseau, Pascal

Study on Oil Film Thickness of Piston Skirt Pattern Coating in A Commercial Vehicle Diesel Engine

2025-01-0397To be published on 10/07/2025

In recent years, there has been a trend towards lower engine speeds and downsizing of diesel engines to improve fuel efficiency. This has the advantage of reducing frictional losses in the hydrodynamic lubrication condition, but causes severe lubrication in the mixed lubrication condition. In order to reduce friction losses without the risk of abnormal wear or seizure, pattern coatings of the piston skirt area have been proposed. In this study, the oil film thickness between piston and cylinder was measured to investigate the effect of pattern coating on the oil film thickness. The oil film thickness between the piston and cylinder were measured by the laser-induced fluorescence method using the optical fibers embedded in the cylinder. The oil film thickness on the piston skirt which had a pattern coating was successfully measured under the condition of high Pmax for the medium duty DI diesel engine. The oil film thickness for the pattern coatings were compared with that for the solid

Tanimoto, Keisuke, Ito, Akemi

The Role of EV Charging Infrastructure in Shaping Energy Pricing and Consumer Behavior – Case Study in Saudi Arabia

2025-01-0421To be published on 10/07/2025

As the electric vehicle (EV) industry grows rapidly in Saudi Arabia, driven by the development of companies such as Ceer, Lucid, and Tesla, there is an increasing need to evaluate and adapt electricity tariff structures to address changing demand patterns. This study explores the interaction between EV charging infrastructure, electricity pricing strategies, and consumer behavior, aiming to provide insights that support the sustainable expansion of the electric mobility ecosystem in the Kingdom. The methodology incorporates demand-supply analysis, energy consumption forecasting, and comparative assessments of tariff models implemented in other countries, with Saudi Arabia serving as a case study aligned with Vision 2030 objectives. Although EV adoption is expected to increase electricity demand, the Kingdom’s generation capacity, which reached 453 TWh in 2023 and is projected to exceed future consumption, ensures a stable and sufficient supply. Currently, public EV charging services

AlJuhani, Haneen Radi A, Bedywi, Lama Mohammed A, AbdulNour, Bashar

Efficient Prediction of Electric Vehicle Battery Temperature

2025-01-0419To be published on 10/07/2025

Maintaining the temperature of lithium-ion batteries within electric vehicles across a wide range of driving scenarios and ambient temperatures is critical for ensuring both safety and long battery life. However, accurately predicting the temperature of batteries that thermally interact with dynamic systems—such as drive cycles, cooling systems, and vehicle components—can be computationally expensive and too slow for the iterative nature of design processes. To address this, our research employs a combination of 1D thermal modeling, a modified lumped capacitance approach, and experimental testing to develop a fast and reliable framework for analyzing battery thermal performance. The model captures the interaction between the drive cycle, cooling plate, coolant flow, thermal interface material, and battery geometry and properties. This hybrid approach balances accuracy and computational efficiency, enabling rapid exploration of thermal design strategies during early-stage vehicle

Builes, Isabel, Bachman, John Christopher, Medina, Mario

Automated Calibration of Heavy-Duty Low NOx Aftertreatment System Controls using Physics-Informed Machine Learning and Global Optimization Methods

2025-01-0402To be published on 10/07/2025

Heavy duty diesel engines provide a robust power plant for transportation applications both on highway and off road. 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 the capability to achieve 0.02 g/bhp-hr. Tailpipe NOx standard through application of a model-based controls in EPA and CARB funded projects. This control mechanism enables precise urea dosing for both steady and transient conditions by leveraging the estimated ammonia storage state in a dual dosing system using chemical kinetics-based SCR observer models. This controller is highly nonlinear, with a significant amount of controller tuning and up to 55 calibratable parameters. To improve the accuracy and reduce the time required for calibration of this controller, this work proposes the deployment of a PINN-based SCR plant model in conjunction with a Genetic Algorithm-based

Chundru, Venkata Rajesh, Rajakumar Deshpande, Shreshta, Sharp, Christopher, Gankov, Stanislav

Impact of the Range Extender Engine Configuration on Powertrain Performance and Vehicle Integration

2025-01-0386To be published on 10/07/2025

The light-duty transportation sector is experiencing a worldwide push towards reduced carbon intensity. One pathway that has been developed focuses on replacing internal combustion engine-based vehicles with full-electric battery electric vehicles (BEV), which offer local CO2-free mobility. However, batteries offer a limited mobility range and require unfavorable long recharging times, leading to a limited range perception among some customers. Range-extended electric vehicles (REEV) utilize a small internal combustion engine to mitigate the range concerns of BEVs, while also enabling a battery size reduction with its associated improvements in cost, weight, and manufacturing CO2 intensity. A previous study by the authors discussed evaluation criteria for range extenders and compared additive technology options to enable cost-, efficiency, or power-optimized REEV applications using a modular approach. This study contrasts the dedicated range extender engine and associated modular

Hoth, Alexander, Peters, Nathan, Bunce, Mike, Marion, Joshua, Silvano, Peter, Pothuraju Subramanyam, Sai

Reinforcement Learning with Adaptive Discount Factor for Clutch Judder Suppression with Stable Learning in Two-Speed EV Transmission

2025-01-0375To be published on 10/07/2025

Designing gear shift control for automotive transmissions requires advanced control techniques to handle nonlinear behaviors that are only partially observable, such as variations in friction coefficients resulting from changes in relative speed between clutch plates and oil temperature fluctuations. Although recent studies employing deep reinforcement learning have effectively suppressed shift shock, they have not sufficiently addressed divergence-type vibrations (judder) arising from the negative gradient of friction coefficients with respect to relative clutch plate speed, which tends to become more pronounced due to clutch plate aging. Conventional reinforcement learning algorithms assume constant state transitions and rewards over time; thus, their learning processes may become unstable when environmental changes occur. Consequently, these methods often fail to stably suppress clutch judder caused by variations in friction coefficients due to repeated clutch engagements. To

Ogawa, Kazuki, Aihara, Tatsuhito, Goto, Takeru, Minorikawa, Gaku

ML-Based System-Level Optimization of an EV Cooling System

2025-01-0376To be published on 10/07/2025

The cooling system of an automobile requires heavy consideration in the design phase, particularly for electric vehicles which have more heat sources than a conventional internal combustion engine. It is in the designer’s best interests to create a cooling system that maintains operating temperatures within optimal limits while consuming less power for better mileage. Furthermore, there are hard limits for EV battery pack temperature that must be maintained to avoid thermal runaway. With the advent of many thermal 1D-CFD commercial simulation software, it has been made possible to simulate these cooling systems with a high degree of accuracy, allowing for several design iterations to be tested and analysed without requiring costly and time-consuming physical testing. These software packages, however, still fall short of creating optimal design iterations of the cooling circuits. This can mainly be attributed to limited optimization algorithms available in the software. Rerunning

Paul, Kavin, Ganesan, Arul, Mansour, Youssef

Reducing Powertrain Software Release Cycles from Months to Days: Streamlined Compliance and Rapid Deployment

2025-01-0379To be published on 10/07/2025

The automotive industry's rapid shift towards electric and connected vehicles intensifies the demand for robust solutions addressing software integrity, cybersecurity, and stringent regulatory compliance, particularly concerning powertrain components and related control units. This paper addresses the significant challenge faced by automotive companies in efficiently managing and deploying an exponentially increasing number of software and hardware variants under the rigorous requirements of UNECE Regulation No. 156. This regulation mandates secure, traceable, and systematic software update processes for new vehicles and its components. The proposed solution demonstrates a transformative approach that significantly reduces the software release cycle for Over-The-Air (OTA) updates from months down to days. By leveraging advanced techniques in automated compliance tracking, efficient parameter management, and centralized documentation, this approach bridges the gap between the software

Sammer, Gerald, Schuch, Nikolaus

Applying Specialized System Analysis for Brake by Wire in Software Defined Vehicles: The Development of a System Analysis Tool (SAT)

2025-01-0355To be published on 09/15/2025

In the rapidly advancing field of automotive engineering, the emergence of Software-Defined Vehicles (SDVs) has introduced complex design and functionality challenges, particularly with respect to braking systems. A main concept of SDV electrical architecture is centralizing vehicle controls and decoupling this control software from sensing and actuation mechanisms. This paradigm shift, specifically when applied to Brake by Wire (BbW) systems, leads to the decentralization of brake actuation, and requires precise coordination among numerous electronic components for effective braking command execution. The absence of mechanical backup in BbW systems necessitates additional fail-safe redundancies, further complicating the system. A comprehensive model that elucidates these component interdependencies is essential for enhancing engineers' optimization of system design. This paper introduces a custom-built System Analysis Tool (SAT), complemented by a specialized methodology, tailored

Heil, Edward, Zuzga, Sean, Babul, Caitlin

Bolstering Driver Braking Confidence – Considerations for “Deceleration Adder” Technologies

2025-01-0353To be published on 09/15/2025

Over the life of a typical vehicle, a average can be expected to apply the brakes on the order of 1.6 million times – almost 9 times per mile and over 290 times per day, and an “exuberant” driver can be expected to do this over 2.2 million times. Without question, the driver becomes accustomed to how the vehicle responds to braking control (and all of the normal variation around it), and even develops expectations for how it will respond the next time the brakes are employed. In the rare event of a failure or malfunction in the brake system, that results in an appreciably different vehicle response to the brake brake input, this can be surprising and even alarming to the driver, sometimes to the extent of causing hesitatation in braking. Fortunately, with the rise of mechatronic braking actuators in the 1980’s and 1990’s, features such as “Driver Brake Assist” (which provides additional pressure beyond what the primary brake actuator can at the time) and “Panic Brake Assist” (which

Antanaitis, David

Preliminary Multi-Physics Modelling and Characterization of a Magneto-Rheological Brake

2025-01-0347To be published on 09/15/2025

Magneto-Rheological Fluid (MRF) is a smart material used in several applications for its ability to switch from fluid behaviour to solid-like conditions if a magnetic field is present. The dependency of viscosity on magnetic field makes this fluid suitable for braking system of electric vehicles, thanks to its high controllability and response time in the whole operative range. The main parameters that influence the behaviour of the fluid, and so the braking action of the system, are magnetic field and rotational velocity. In general, the variable physical properties make it complicated to simulate the system and its behaviour in different operating conditions. Therefore, it is usually necessary to build a physical prototype to experimentally verify the response of the braking system at different driving conditions. This paper presents the development of a virtual model of Magneto-Rheological Brakes (MRB) whose validity is extended to different driving conditions. This can be

De Luca, Elena, Imberti, Giovanni, de Carvalho Pinheiro, Henrique, Carello, Massimiliana

Effect of Casting Microstructure on the Mechanical Performance of Recycled EN AC-43200 Al-Si Alloy

2025-01-0357To be published on 09/15/2025

Nowadays, the automotive industry is moving toward the reduction of CO2 emissions implementing different strategies. Beyond the direct reduction of emissions from the vehicles, an important role is played by the production of parts made with recycled materials. This is particularly relevant for automotive components (e.g., brake calipers and steering knuckles) produced using cast Aluminium-Silicon (Al-Si) alloys, whose primary production from bauxite is highly energy-intensive. However, recycled cast Al-Si alloys could have different mechanical performances with respect to their primary counterparts, due to the presence of impurity elements from the recycling process. For this reason, it becomes fundamental to study the effect of different casting parameters (e.g., molten alloy temperature, sprue design and mould temperature) on the solidification microstructure of recycled, cast Al-Si alloys and, as a consequence, on the mechanical performances of the material. In this context, this

Pavesi, Arianna, Barella, Silvia, D'Errico, Fabrizio, Bonfanti, Andrea, Bertasi, Federico

Enhancing Robustness of Electro-Hydraulic Brake-by-Wire Actuators via Linear Active Disturbance Rejection Control

2025-01-0341To be published on 09/15/2025

In recent years, motorsport has increasingly focused on environmental concerns, leading to the rise of hybrid and fully electric competitions. In this scenario, electric motors and batteries take a crucial role in reducing the environmental impact by recovering energy during braking. However, due to inherent limitations, motors and battery cannot fully capture all braking power, necessitating the use of standard friction brakes. To achieve an efficient balance between electric motors and friction brakes, the brake pressure can no longer be directly controlled by the driver. Instead, it must be computed by the Vehicle Control Unit (VCU) and sent to a smart actuator, i.e. the Brake-By-Wire (BBW), which ensures that the required pressure is applied. The standard approach to achieve precise pressure control is to design a nested Proportional-Integral-Derivative (PID) control architecture, which requires an accurate nominal model of the system dynamics to meet the desired tracking

Gimondi, Alex, Dubbini, Alberto, Riva, Giorgio, Cantoni, Carlo

Dynamic analysis of automotive wheel bearings

2025-01-0366To be published on 09/15/2025

Bearings are mechanical components that support loads and transmit rotational motion. With the increasing demand for high-value-added products, such as semiconductors, aerospace components, and robotics, the need for more precise and diverse applications has grown. Consequently, accurate bearing performance prediction and evaluation technologies have become essential. Bearing performance prediction is generally classified into static and dynamic approaches. Traditionally, research has primarily focused on static and quasi-static predictions based on bearing theory. However, these methods have a significant limitation in that they fail to accurately consider the actual behavior of bearings. As a result, the necessity for prediction methods based on numerical analysis, which can account for the time-dependent behavior of bearings, has been increasingly recognized. In this study, dynamic analysis of bearings was conducted to evaluate their behavior over time. First, dynamic analysis of

Lee, Seungpyo

A Study on the Development of Optimal Brakes for Electric Vehicles Using Simulation

2025-01-0345To be published on 09/15/2025

As the internal combustion engine vehicle change into the electric vehicle, we can use regenerative brake. It can improve not only the energy consumption, but also reduce the hydraulic brake usage. The less hydraulic brake usage mitigates the heat load on the brake disc. From this reason, the lightweight brake can be used in the electric vehicle. However, when the lightweight brake is applied, the brake NVH can be increased. The optimization design of the lightweight brake should be done to prevent the brake NVH. In this paper, the optimal brake disc thickness and brake interfaces are determined by using of disc heat capacity analysis. The lightweight brake should be optimized by using of the brake squeal analysis. We can verify the results from both analysis and tests. Finally, we can have the lightweight brake, which is competitive in terms of cost, weight and robust to the brake NVH

Kim, Sungho, Kim, Jeongkyu, Hwang, Jaekeun, Kang, Donghoon

An Investigation of a Battery Module Thermal Behaviour Based on CFD Simulations and Experimental Tests

2025-24-0144To be published on 09/07/2025

Battery management systems are the key component in electric vehicles (EVs), which are increasingly replacing internal combustion engine (ICE) vehicles in the automotive industry. Battery management systems mainly focus on battery thermal management, efficiency, battery life and the safety conditions. Generally, lithium-ion batteries have been chosen in EV cars. Therefore, the internal resistance of Li-ion batteries plays a crucial role in the thermal behaviour. Most of the published studies rely on 0D-1D models to analyse single cell thermal behaviour depending on the internal resistance at different ambient temperatures and charging/ discharging rates, and on the cooling system However, these models, though fast, cannot provide detailed information about the temperature distribution within a cell or a module. Full 3D CFD-CHT simulations on the other hand, are very time consuming and require highly qualified computers, but allow a deeper understanding of the cell/module thermal

Karaca, Cem, Olmeda, Pablo, Margot, Xandra, Postrioti, Lucio, Baldinelli, Giorgio

Reducing Range Prediction Uncertainty in Heavy-Duty Electric Vehicles Using a Route-Informed Transformer-Based Model

2025-24-0122To be published on 09/07/2025

Electrification of heavy-duty on-road trucks used for regional freight transportation is a viable option for fleets to reduce operational and maintenance costs and lower their carbon footprint. However, there is considerable uncertainty in projecting their daily range because highly variable payload mass, among other factors, confounds battery state of charge (SOC) prediction algorithms. Previous work by the authors proposed an electric vehicle range prediction model based on two parallel recurrent neural networks (RNNs). The first RNN used mean-variance estimation to output a predicted mean and variance, and the second used bounded interval estimation to provide bounds on the SOC required to complete a trip. The dual RNN approach resulted in estimating the remaining range and error bands of the SOC over the route. The previous work was limited because it did not incorporate driving conditions, like road type and ambient temperature, that affect driver behavior and energy consumption

Jayaprakash, Bharat, Eagon, Matthew, Northrop, William F.

Design of a Reconfigurable Winding Switch for an In-Wheel Automotive Motor

2025-24-0130To be published on 09/07/2025

A design is presented for a mechanical switchgear, intended for reconfiguring the windings of an electric machine whilst in operation. The design is a result of the EM-TECH project funded under Horizon Europe, and includes integration onto an in-wheel automotive motor. The motor features 6 phase fractions, which can be reconfigured by the switchgear between series-star or parallel-star arrangements, thereby doubling the torque or speed range of the electric machine. The effect on the operating envelope of the machine is similar to the addition of a 2-speed transmission, but with an added mass of only 1.5kg – around one tenth of the equivalent transmission. As well as the extended operating envelope, the reconfigurable winding motor offers benefits in efficiency and power density. Previous studies have shown the technical feasibility of such devices using semiconductor switches. Although these studies have confirmed the performance of the technology, such semiconductor solutions have

Vagg, Christopher, Thomas, Luke, Pickering, Simon, Herzog, Matic, Trinchuk, Danylo, Romih, Jaka

Practical Mixed Parameter Obtention Framework for Li-Ion Battery Electrochemical and Degradation Models Based on Parameter Classification and Physical Measurement

2025-24-0141To be published on 09/07/2025

Prediction of EV performance through lifetime is a crucial task. However, accurate prediction of states of LIBs remains a challenge due to the complexity of detailed electrochemical models, absence of a single universally accepted approach for the identification of model parameters and limitations in invasive and non-invasive parameter obtention methods. Classification and estimation of the most relevant parameters under different steps will enhance the identifiability of parameters in P2D models operating under various conditions. On the other hand, reliable estimation of the internal state of batteries can be drawn with proper integration of material parameters into the battery model. In this study, a systematic classification framework of parameter obtention was proposed through multi-steps for P2D electrochemical and degradation models. Furthermore, a practical mixed approach is developed for parameter obtention of P2D models with optimization-based calibration methodology and

Mehranfar, Sadegh, Mahmoudzadeh Andwari, Amin, Garcia, Antonio, Micó, Carlos, Elkourchi, Imad, Bekaert, Emilie, Herran, Alvaro, Konno, Juho

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