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Technical Paper

Turbocharging system selection for a hydrogen-fuelled spark-ignition internal combustion engine for heavy-duty applications

2024-07-02
2024-01-3019
Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.
Technical Paper

Aerodynamics' Influence on Performance in Human-Powered Vehicles for Sustainable Transportation

2024-06-12
2024-37-0028
The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.
Technical Paper

Development of a Soft-Actor Critic Reinforcement Learning Algorithm for the Energy Management of a Hybrid Electric Vehicle

2024-06-12
2024-37-0011
In recent years, the urgent need to fully exploit the fuel economy potential of the Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) have led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure, in which an agent is able to learn the optimal control strategy through the feedback received by a direct interaction with the environment. Therefore, in this study, a new Soft Actor-Critic agent (SAC), which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability.
Technical Paper

Design of a Decentralized Control Strategy for CACC Systems accounting for Uncertainties

2024-06-12
2024-37-0010
Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.
Technical Paper

Artificial Neural Network for Airborne Noise Prediction of a Diesel Engine

2024-06-12
2024-01-2929
The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points).
Technical Paper

Coordinated Charging and Dispatching for Large-Scale Electric Taxi Fleets Based on Bi-Level Spatiotemporal Optimization

2024-04-09
2024-01-2880
The operation management of electric Taxi fleets requires cooperative optimization of Charging and Dispatching. The challenge is to make real-time decisions about which is the optimal charging station or passenger for each vehicle in the fleet. With the rapid advancement of Vehicle Internet of Things (VIOT) technologies, the aforementioned challenge can be readily addressed by leveraging big data analytics and machine learning algorithms, thereby contributing to smarter transportation systems. This study focuses on optimizing real-time decision-making for charging and dispatching in large-scale electric taxi fleets to improve their long-term benefits. To achieve this goal, a spatiotemporal decision framework using Bi-level optimization is proposed. Initially, a deep reinforcement learning-based model is built to estimate the value of charging and order dispatching under uncertainty.
Technical Paper

Research on Automatic Removal of Outliers in Fuel Cell Test Data and Fitting Method of Polarization Curve

2024-04-09
2024-01-2896
Fuel cell vehicles have always garnered a lot of attention in terms of energy utilization and environmental protection. In the analysis of fuel cell performance, there are usually some outliers present in the raw experimental data that can significantly affect the data analysis results. Therefore, data cleaning work is necessary to remove these outliers. The polarization curve is a crucial tool for describing the basic characteristics of fuel cells, typically described by semi-empirical formulas. The parameters in these semi-empirical formulas are fitted using the raw experimental data, so how to quickly and effectively automatically identify and remove data outliers is a crucial step in the process of fitting polarization curve parameters. This article explores data-cleaning methods based on the Local Outlier Factor (LOF) algorithm and the Isolation Forest algorithm to remove data outliers.
Technical Paper

4D Radar-Inertial SLAM based on Factor Graph Optimization

2024-04-09
2024-01-2844
SLAM (Simultaneous Localization and Mapping) plays a key role in autonomous driving. Recently, 4D Radar has attracted widespread attention because it breaks through the limitations of 3D millimeter wave radar and can simultaneously detect the distance, velocity, horizontal azimuth and elevation azimuth of the target with high resolution. However, there are few studies on 4D Radar in SLAM. In this paper, RI-FGO, a 4D Radar-Inertial SLAM method based on Factor Graph Optimization, is proposed. The RANSAC (Random Sample Consensus) method is used to eliminate the dynamic obstacle points from a single scan, and the ego-motion velocity is estimated from the static point cloud. A 4D Radar velocity factor is constructed in GTSAM to receive the estimated velocity in a single scan as a measurement and directly integrated into the factor graph. The 4D Radar point clouds of consecutive frames are matched as the odometry factor.
Technical Paper

Simulative Assessments of Cyclic Queuing and Forwarding with Preemption in In-Vehicle Time-Sensitive Networking

2024-04-09
2024-01-1986
The current automotive industry has a growing demand for real-time transmission to support reliable communication and for key technologies. The Time-Sensitive Networking (TSN) working group introduced standards for reliable communication in time-critical systems, including shaping mechanisms for bounded transmission latency. Among these shaping mechanisms, Cyclic Queuing and Forwarding (CQF) and frame preemption provide deterministic guarantees for frame transmission. However, despite some current studies on the performance analysis of CQF and frame preemption, they also need to consider the potential effects of their combined usage on frame transmission. Furthermore, there is a need for more research that addresses the impact of parameter configuration on frame transmission under different situations and shaping mechanisms, especially in the case of mechanism combination.
Technical Paper

A Method for Identifying the Noise Characteristics of an Electric Motor System Based on Tests Conducted under Distinct Operating Conditions

2024-04-09
2024-01-2334
The noise tests of electric motor systems serve as the foundation for studying their acoustic issues. However, there is currently a lack of corresponding method for identifying key noise characteristics, such as the noise frequency range that needs to be considered, the significant noise order, and the resonance band worth paying attention to, based on experimental test data under actual operating conditions. This article proposes a method for identifying the noise characteristics of an electric motor system based on tests conducted under distinct operating conditions, which consists of three parts: identifying the primary frequency range, the significant order, and the important resonance band. Firstly, in order to extract noise with the primary energy, the concept of noise contribution is introduced. The primary frequency range and the significant order under a specific operating condition can be obtained after extraction.
Technical Paper

Braking Judder Test and Simulation Analysis of Commercial Vehicle

2024-04-09
2024-01-2342
Brake judder affects vehicle safety and comfort, making it a key area of research in brake NVH. Transfer path analysis is effective for analyzing and reducing brake judder. However, current studies mainly focus on passenger cars, with limited investigation into commercial vehicles. The complex chassis structures of commercial vehicles involve multiple transfer paths, resulting in extensive data and testing challenges. This hinders the analysis and suppression of brake judder using transfer path analysis. In this study, we propose a simulation-based method to investigate brake judder transfer paths in commercial vehicles. Firstly, road tests were conducted to investigate the brake judder of commercial vehicles. Time-domain analysis, order characteristics analysis, and transfer function analysis between components were performed.
Technical Paper

Assessing the Effects of Computational Model Parameters on Aerodynamic Noise Characteristics of a Heavy-Duty Diesel Engine Turbocharger Compressor at Full Operating Conditions

2024-04-09
2024-01-2352
In recent years, with the development of computing infrastructure and methods, the potential of numerical methods to reasonably predict aerodynamic noise in turbocharger compressors of heavy-duty diesel engines has increased. However, aerodynamic acoustic modeling of complex geometries and flow systems is currently immature, mainly due to the greater challenges in accurately characterizing turbulent viscous flows. Therefore, recent advances in aerodynamic noise calculations for automotive turbocharger compressors were reviewed and a quantitative study of the effects for turbulence models (Shear-Stress Transport (SST) and Detached Eddy Simulation (DES)) and time-steps (2° and 4°) in numerical simulations on the performance and acoustic prediction of a compressor under various conditions were investigated.
Technical Paper

Analysis and Design of Suspension State Observer for Wheel Load Estimation

2024-04-09
2024-01-2285
Tire forces and moments play an important role in vehicle dynamics and safety. X-by-wire chassis components including active suspension, electronic powered steering, by-wire braking, etc can take the tire forces as inputs to improve vehicle’s dynamic performance. In order to measure the accurate dynamic wheel load, most of the researches focused on the kinematic parameters such as body longitudinal and lateral acceleration, load transfer and etc. In this paper, the authors focus on the suspension system, avoiding the dependence on accurate mass and aerodynamics model of the whole vehicle. The geometry of the suspension is equated by the spatial parallel mechanism model (RSSR model), which improves the calculation speed while ensuring the accuracy. A suspension force observer is created, which contains parameters including spring damper compression length, push rod force, knuckle accelerations, etc., combing the kinematic and dynamic characteristic of the vehicle.
Technical Paper

Performance Parity Study of Electrified Class 8 Semi Trucks with Diesel Counterparts

2024-04-09
2024-01-2164
It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.
Technical Paper

Rapid assessment of power battery states for electric vehicles oriented to after-sales maintenance

2024-04-09
2024-01-2201
With the continuous popularization of electric vehicles (EVs), ensuring the best performance of EVs has become a significant concern, and lithium-ion power batteries are considered as the essential storage and conversion equipment for EVs. Therefore, it is of great significance to quickly evaluate the state of power batteries. This paper investigates a fast state estimation method of power batteries oriented to after-sales and maintenance. Based on the battery equivalent circuit model and heuristics optimization algorithm, the battery model parameters, including the internal ohmic and polarization resistance, can be identified using only 30 minutes of charging or discharging process data without full charge or discharge. At the same time, the proposed method can directly estimate the state of charge (SOC) and maximum available capacity of the battery without knowing initial SOC information.
Technical Paper

Uniformity Identification and Sensitivity Analysis of Water Content of Each PEM Fuel Cell Based on New Online High Frequency Resistance Measurement Technique

2024-04-09
2024-01-2189
Water content estimation is a key problem for studying the PEM fuel cell. When several hundred fuel cells are connected in serial and their active surface area is enlarged for sufficient power, the difference between cells becomes significant with respect to voltage and water content. The voltage of each cell is measurable by the cell voltage monitor (CVM) while it is difficult to estimate water content of the individual. Resistance of the polymer electrolyte membrane is monotonically related to its water content, so that the new online high frequency resistance (HFR) measurement technique is investigated to identify the uniformity of water content between cells and analyze its sensitivity to operating conditions in this paper. Firstly, the accuracy of the proposed technique is experimentally validated to be comparable to that of a commercialized electrochemical impedance spectroscopy (EIS) measurement equipment.
Technical Paper

Revealing the Impact of Mechanical Pressure on Lithium-Ion Pouch Cell Formation and the Evolution of Pressure During the Formation Process

2024-04-09
2024-01-2192
The formation is a crucial step in the production process of lithium-ion batteries (LIBs), during which the solid electrolyte interphase (SEI) is formed on the surface of the anode particles to passivate the electrode. It determines the performance of the battery, including its capacity and lifetime. A meticulously designed formation protocol is essential to regulate and optimize the stability of the SEI, ultimately achieving the optimal performance of the battery. Current research on formation protocols in lithium-ion batteries primarily focuses on temperature, current, and voltage windows. However, there has been limited investigation into the influence of different initial pressures on the formation process, and the evolution of cell pressure during formation remains unclear. In this study, a pressure-assisted formation device for lithium-ion pouch cells is developed, equipped with pressure sensors.
Technical Paper

Application of a CFD Methodology for the Design of PEM Fuel Cell at the Channel Scale

2024-04-09
2024-01-2186
Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.
Technical Paper

Efficient Fatigue Performance Dominated Optimization Method for Heavy-Duty Vehicle Suspension Brackets under Proving Ground Load

2024-04-09
2024-01-2256
Lightweight design is a key factor in general engineering design practice, however, it often conflicts with fatigue durability. This paper presents a way for improving the effectiveness of fatigue performance dominated optimization, demonstrated through a case study on suspension brackets for heavy-duty vehicles. This case study is based on random load data collected from fatigue durability tests in proving grounds, and fatigue failures of the heavy-duty vehicle suspension brackets were observed and recorded during the tests. Multi-objective fatigue optimization was introduced by employing multiaxial time-domain fatigue analysis under random loads combined with the non-dominated sorting genetic algorithm II with archives.
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