bluuebunny/crossref_metadata_2025 huggingface dataset:
Emission Control on a Dual Model Hybrid Passenger Car to Meet China 6 Legislation
Authors: Chen Jian , Wang Xuhua , Liu Yi
Published: April 2024

With the increasing number of hybrid vehicles in the Chinese market, research on aftertreatment systems for hybrid vehicles has become very popular. China has currently implemented national on-road China 6 regulations for emission control of all gasoline and diesel vehicles, including hybrid ones. So far, there are few papers on the optimization of aftertreatment for hybrid gasoline vehicles. Due to the introduction of electric motors in hybrid vehicles, the engine starts frequently and leads to inconsistent stability of engine operating conditions and brings the challenge to emission control of engine exhaust. This article selects a highly popular hybrid gasoline vehicle in China for research, which is a dual-mode hybrid (DM hybrid) passenger car. There is an obvious correlation between the emissions between the driving pattern and the hybrid strategy. The catalyst temperature is the main influencing factor on the performance of TWC catalysts, while the higher exhaust temperature brings the better conversion efficiency of pollutants. Since less thermal energy is needed to heat up the low mass substrate, the light-off performance of catalyst with same platinum group metals (PGM) loading is achieved earlier. As applied in the DM hybrid vehicle aftertreatment system, the low mass substrate can achieve 10~30% better performance in gaseous emissions reduction on China VI regulated cycle, Worldwide Harmonized Light Vehicles Test Cycle (WLTC), compared to the standard substrate both for fresh and aged catalyst samples. The catalyst coated on low mass substrate also enabled good Real Driving Emissions (RDE) result to meet China 6b.
Stress-Constrained Multi-Material Topology Optimization
Authors: Shi Yifan , Huang Yuhao , Morris Zane , Teoli Mira , Tameer Daniel , Kim Il Yong
Published: April 2024

The study and application of Topology Optimization (TO) has experienced great maturity in recent years, presenting itself as a highly influential and sought-after design tool in both the automotive and aerospace industries. TO has experienced development from single material topology optimization (SMTO) to multi-material topology optimization (MMTO), where material selection is simultaneously optimized with material existence. Today, MMTO for standard structural optimization responses are well supported. An additional and vital response in the design of structures is that of stress. Stress-driven or stress-controlled optimization techniques for SMTO are well understood and have been well-documented, evidenced by both published works and its availability in multiple commercial solvers. However, its integration into MMTO frameworks has not yet achieved reliable levels of accuracy and flexibility. The principal limitation of existing stress-constrained MMTO methodologies is the inability to consider candidate material-specific stress limits. Another limitation is that candidate materials cannot have different Poisson’s ratios. Herein, the study of stress-constrained MMTO is extended to consider material-specific yield stresses by introducing a novel stress limit interpolation scheme on P-norm aggregation scheme. Moreover, a stress correction method is extended from SMTO to MMTO, to avoid the stress overestimation issue. In support of the discussion on the constraint and its characteristics, its sensitivities are derived. The proposed method is examined on both 2D and 3D models, including the comparison to the results obtained by the existing commercial solver and on models with more than one million elements or multiple load cases to present the effectiveness of the proposed method.
Effects of Traffic Control Device and Hazard Location on Fixations During Intersection Navigation: A Simulator Study
Authors: Caren Brooklin , Ziraldo Erika , Oliver Michele
Published: April 2024

Collisions resulting in injuries or fatalities occur more frequently at intersections. This is partly because safe navigation of intersections requires drivers to accurately observe and respond to other road users with conflicting paths. Previous studies have raised questions about how traffic control devices and the positioning of other road users might affect drivers' visual search strategies when navigating intersections.

To address these questions, four left-turn-across-path (LTAP) scenarios were created by combining two types of traffic control devices (stop signs and traffic lights) with two hazard starting locations (central and peripheral). Seventy-four licensed drivers responded to all scenarios in a counterbalanced order using a full vehicle driving simulator. Eye-tracking glasses were used to monitor eye movements, both before and after hazard onset.

The results revealed that drivers at the signalized intersections took longer to fixate the LTAP hazard before onset, spent less time fixated on the hazard, and made fewer visits to the hazard compared to drivers at the unsignalized, stop-sign controlled intersections. There were no significant main effects of hazard location on the eye tracking measures, however, there was an interaction between the traffic control device and the hazard location on total fixation duration. Participants fixated the signal-controlled hazards longer in the central location but fixated the stop-sign controlled hazards longer in the peripheral location.

Despite the inherent risks of intersecting traffic, results indicate the drivers at signalized intersections rely heavily on the traffic control device to prevent collisions. Given the high speed and traffic volume at signalized intersections, these results can be used to justify the implementation of measures such as protected left turn signals and other infrastructure changes aimed at reducing the frequency and severity of LTAP collisions.
A Proposed Method for Determination of Distal Tibia Fracture Tolerance for Prediction of Ankle Injuries
Authors: Noss Junior , Donlon John-Paul , Hallman Jason , Carpenter Randolff , Forman Jason
Published: April 2024

Ankle injuries continue to occur in motor vehicle collisions, particularly in female occupants. The causes of these injuries are sometimes unclear. Further understanding of ankle fracture tolerance and refinement of ankle injury prediction tools would help future injury prediction efforts. The goal of this study was to identify ankle injury types of interest and develop a test methodology to induce these injuries. Cases were examined from NHTSA’s Crash Injury Research Engineering Network (CIREN) database. 68 cases with distal tibia fracture were identified from CIREN years 2017+ (vehicle models years 2010+). The most common fractures were pilon fractures and malleolar fractures. Based on these results, a test methodology was developed to induce pilon and medial malleolar fractures in isolated cadaveric tibiae to quantify local fracture tolerance. Nineteen post-mortem human subject (PMHS) specimens (9 male and 10 female across a wide anthropometric range) were tested. To replicate the fractures, a novel method was developed to subject isolated distal tibia specimens to inferomedial oblique loading via stainless steel, 3D-printed, subject-specific, metallic pseudo-tali. These pseudo-tali were chosen to produce loading similar to what would occur from ankle eversion under compression, driving the talus into the distal tibia. Pilon fractures and medial malleolus fractures were produced, with fracture patterns similar to those observed in the CIREN cases. Boundary forces and moments, pseudo-tali displacements and rotations, and fracture timing (via high-speed video) were measured. Pre- and post- fracture bone geometry was digitized via computed tomography (CT) scans. These results demonstrated the utility of these novel methods and will help facilitate future implementation of tissue-level fracture prediction in the distal tibia of human body models, advancing future ability to predict ankle injury risk under complex loading.
Vehicle Seat Occupancy Detection and Classification Using Capacitive Sensing
Authors: Prasanna Kumar Rahul , Melcher David , Buttolo Pietro , Jia Yunyi
Published: April 2024

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type. This paper details the working of the proposed technique in monitoring vehicle seat occupancy statuses non-intrusively and presents experimental results to validate the technique’s effectiveness in meeting performance expectations.
Computational Study of a DrivAer Model by Using the Partially-Averaged Navier-Stokes Approach in Combination with the Immersed Boundary Method
Authors: Basara Branislav , Pavlovic Zoran , Saric Sanjin
Published: April 2024

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the Finite Volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1, 2]. In that work, it was shown that the same accuracy of predicted aerodynamic forces could be achieved for both types of computational meshes, the standard body-fitted mesh and the immersed boundary (IB) Cartesian mesh, by using the Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model as well as by using the Partially-Averaged Navier-Stokes (PANS) method. Based on the accuracy achieved, Basara et al. [2] concluded that further work could focus on evaluating the turbulence modelling on the immersed boundary meshes only. Furthermore, due to all the known shortcomings of the steady-state approach, in this work we only deal with the Partially Averaged Navier-Stokes (PANS), which belongs to the hybrid RANS-LES (scale resolving/high fidelity) methods. Therefore, we analyze instantaneous and time-averaged results obtained on different meshes (150-300 million computational cells) to show how PANS calculations improve with the mesh refinement and consequently with the resolution of more scales of motion. Comparisons of the PANS results with the experimental data for the well-known DrivAer notchback model (Hupertz et al. [3]) demonstrate the predictive capability of PANS.
Research on Distributed Drive Electric Vehicle Lane Change Trajectory Tracking Control Based on MPC
Authors: Xiao Bin , Zou Xiaojun , Song Wei , Wang Tao , Wang Liangmo , Zong Yuhua
Published: April 2024

Distributed drive electric vehicles (DDEVs), characterized by independently controllable torque at each wheel, redundant actuators, and highly integrated drive systems, are considered as the optimal platform for achieving intelligent driving with high safety and efficiency. This paper focuses on the trajectory tracking and lateral stability coordination control problems in high-speed emergency collision avoidance and autonomous lane change scenarios for DDEVs. A trajectory tracking control algorithm is proposed based on model predictive control (MPC) and coordinated optimization of distributed drive torques. The method adopts a hierarchical control architecture. Firstly, the upper-level trajectory planning layer calculates the lane change trajectory data. Based on the trajectory planning results, the middle-level controller designs a time-varying linear model predictive control method to solve the desired front wheel steering angle and additional yaw moment. Then, considering the modeling uncertainty of the steering actuator and road disturbances, a front wheel steering angle tracking strategy based on sliding mode variable structure control is designed. The lower-level controller aims to minimize tire loading rate to maximize vehicle stability margin and utilizes an active set algorithm to achieve four-wheel torque optimization allocation. Finally, a four-wheel hub motor-driven electric vehicle is taken as the research object. The effectiveness and real-time performance of the proposed control method are validated through simulations on the CarSim/Simulink co-simulation platform under high-speed lane change and double-lane change conditions.
Vehicle Trajectory Planning and Control Based on Bi-Level Model Predictive Control Algorithm
Authors: Liu Xingchen , Kang Kailei , Liu Xinhong
Published: April 2024

Autonomous driving technology represents a significant direction for future transportation, encompassing four key aspects: perception, planning, decision-making, and control. Among these aspects, vehicle trajectory planning and control are crucial for achieving safe and efficient autonomous driving. This paper introduces a Combined Model Predictive Control algorithm aimed at ensuring collision-free and comfortable driving while adhering to appropriate lane trajectories. Due to the algorithm is divided into two layers, it is also called the Bi-Level Model Predictive Control algorithm (BLMPC). The BLMPC algorithm comprises two layers. The upper-level trajectory planner, to reduce planning time, employs a point mass model that neglects the vehicle's physical dimensions as the planning model. Additionally, obstacle avoidance cost functions are integrated into the planning process. In the upper trajectory planner, the fifth-order polynomial algorithm is also used to smooth the planned trajectory to meet the requirements of vehicle dynamics and passenger comfort. The lower-level trajectory tracker is responsible for real-time trajectory tracking and control, and the paper conducts experiments comparing the Model Predictive Control (MPC) algorithm with the Linear Quadratic Regulator (LQR) algorithm, under the premise of considering the feasibility, cost and safety of the experiment, the front wheel steering Ackerman experimental car is selected as the experimental carrier to verify the reliability of the MPC trajectory tracking control algorithm and ensure the stable driving of the vehicle along the planned trajectory. To address complex road environments, a dynamic obstacle avoidance algorithm is incorporated during the trajectory planning phase. This algorithm allows the vehicle to rapidly generate collision-free trajectories when encountering obstacles, utilizing techniques such as envelope polygonal distance and anti-roll constraints. Compared with other trajectory planning algorithms, the MPC algorithm used in this paper can better adapt to the uncertainty of the system and has better robustness in the face of external disturbances. Finally, the proposed approach is validated through simulation experiments using the Carsim-Simulink co-simulation tool at four different speeds: 10 m/s, 20 m/s, 30 m/s, and 40 m/s. The results demonstrate that the BLMPC algorithm not only ensures safe and comfortable driving but also exhibits high planning efficiency and obstacle avoidance performance in complex road environments. This research provides valuable guidance for advancing autonomous driving technology and its practical implementation
Remote Control Autonomous Driving System
Authors: Iwahori Kento , Sawano Takuro , Iwazaki Noritsugu , Kanou Takeshi , Inoue Go , Okamoto Yuki , Hatano Yasuyoshi , Yasuyama Shogo , Kato Junya , Oka Yuhei , Kakuma Daisuke , Yajima Amane , Chiba Hiroya
Published: April 2024

The concept of the vehicle has changed in accordance with the technological innovations on last decade. Today we can call these changes basically as "CASE" (Connected, Autonomous/Automated, Shared, and Electric). The ease of product access on the user side and the mass production related works have increased worldwide production volumes. This issue has resulted in a greater demand for manpower in the sector. In addition, management, productivity, and profitability related difficulties have occurred. In this project, improvements were made mainly around the productivity through the automation of "vehicle transfer operations in plant operations", which is one of a major problem and a manpower/hour consuming task. This system named as Remote-Control Auto Driving System (RCD). The advance technology used system enabling unmanned, secured operations, were implemented in mass production environment earlier than the rest of the world.
Comparative Analysis of Clustering Algorithms Based on Driver Steering Characteristics
Authors: Chen Chen , Zong Changfu
Published: April 2024

Driver steering feature clustering aims to understand driver behavior and the decision-making process through the analysis of driver steering data. It seeks to comprehend various steering characteristics exhibited by drivers, providing valuable insights into road safety, driver assistance systems, and traffic management. The primary objective of this study is to thoroughly explore the practical applications of various clustering algorithms in processing driver steering data and to compare their performance and applicability. In this paper, principal component analysis was employed to reduce the dimension of the selected steering feature parameters. Subsequently, K-means, fuzzy C-means, the density-based spatial clustering algorithm, and other algorithms were used for clustering analysis, and finally, the Calinski-Harabasz index was employed to evaluate the clustering results. Furthermore, the driver steering features were categorized into lateral and longitudinal categories. Different clustering algorithms were selected for clustering analysis to assess potential differences between lateral and longitudinal steering features and to determine the applicability of various algorithms for this purpose. In the comparative analysis, we comprehensively evaluate the performance of various algorithms in terms of clustering quality, interpretability, computational efficiency, and applicability. Selecting algorithms suitable for specific tasks and datasets is crucial to enhancing computational efficiency and the quality of clustering results. Through the comparative analysis of the driver steering feature clustering algorithm, a deeper understanding of the steering behavior mode can be obtained, providing support for optimizing the driver assistance system, advancing automatic driving technology, enhancing the driving experience, optimizing traffic management, and ultimately realizing a more intelligent and safer road traffic system.
Numerical Investigation on Heat Dissipation Performance of Multi-Fan Cooling Module
Authors: Guo Yi Ming , Xiao Bin , Huang Yu , Li Guoqiang , Shangguan Wen-Bin
Published: April 2024

To study the heat dissipation performance of the multi-fan cooling module composed of multiple fans and a radiator, numerical models of the radiator and the multi-fan cooling module were established, and heat dissipation performance prediction analysis and application analysis were conducted. In modeling, the Effectiveness-Number of Transfer Units (ε − NTU) method is used to predict the heat dissipation performance of the radiator. The aerodynamic performance of the fan at any speed is obtained by the similarity theorem using the data obtained from the tests at a certain speed. The influence between the fan and the radiator was established by using the flow addition scheme. To validate the established model, heat dissipation performance using 36 radiators and 11 multi-fan cooling modules is measured, and the measured data are compared with the calculations. The results show that: (1) For the radiator model, relative errors of heat dissipation are below 15.03%, and the absolute error of the outlet temperature is less than 1.6 °C. (2) For the multi-fan cooling module Relative errors of heat dissipation are within 13.34%-18.35%, and the absolute error of the outlet temperature is less than 4.3 °C. Considering the difficulty of obtaining the radiator structural parameters, the ε − NTU model with a semi-empirical formula with multiple sets of operation points as input is proposed, and the model verification error is below 6.86%. This method can predict the heat dissipation of different core sizes, and the calculation error is within 20%. For fan control, this article demonstrates that partial activation of the fan is beneficial to reducing fan energy consumption under low heat source conditions.
High Pressure Hydrogen Injector Sizing Using 1D/3D CFD Modeling for a Compression Ignition Single Cylinder Research Engine
Authors: Mancaruso Ezio , Catapano Francesco , Rossetti Salvatore , Anaclerio Giuseppe , Camporeale Sergio , Episcopo Domenico , Laera Davide , Torresi Marco
Published: April 2024

With the aim of decarbonizing the vehicles fleet, the use of hydrogen is promising solution. Hydrogen is an energy carrier, carbon-free, with high calorific value and with no CO2 and HC emissions burning in ICE. Hydrogen use in spark ignition engines has already been extensively investigated and optimized. On the other hand, its use in compression ignition engines has been little developed and, therefore, there is a lack of information regarding the combustion in ultra-lean conditions, typical of diesel engines.

Several applications employ dual fuel combustion for the easy management of the PFI injection system to be applied in addition to the DI Common Rail system. However, this mode suffers from several problems regarding the management of the maximum flow rate of hydrogen into the intake. In particular, to avoid throwing hydrogen into the exhaust, injection must be started after the valve crossing. Furthermore, it is not possible to introduce gaseous fuel into the engine when the compression phase begins. In fact, the hydrogen can find favorable autoignition conditions, giving rise to unwanted combustion processes in the manifold.

For these reasons, a direct hydrogen injection system that could be easily applied to the head of the production engine has been designed and realized. In the head of 1.9l GM engine mounted on a single cylinder research engine, the adapter in place of the pre-heating glow plug has been modified to accommodate a commercial injector for the hydrogen direct injection up to 100 bar. Hydrogen is provided by a bottle at 200 bar via a secured line and a rail prior to reach the injector.

In the design stage, attention has been paid to the correct assessment of the optimum diameter of the injection system. A 1D Fanno flow based model has been developed to determine in a quick way the mass flow rate and total pressure losses for several possible diameters. In particular, in order to have the desired hydrogen quantity entering into the cylinder a probe featured by a diameter of 2 mm and length of 137 mm has been identified. To confirm the validity of the 1D result, the CAD model of injection system has been designed and analyzed by means of computational fluid-dynamic simulations, which have shown a good agreement with the 1D outcomes. Thus, the 1D Fanno model can be considered a fast and reliable tool for the preliminary design of injection systems for gaseous fuels.
Full-Scale CFD Prediction of the Performance of Advanced After-Treatment Systems during Severe RDE Test Cycle
Authors: Sartirana Andrea , Montenegro Gianluca , Della Torre Augusto , Onorati Angelo , Pace Lorenzo , Zaldua-Moreno Naroa
Published: April 2024

Air pollution is a significant environmental issue, and exhaust emissions from internal combustion engines are one of the primary sources of harmful pollutants. The transportation sector, which includes road vehicles, contributes to a large share of these emissions. In Europe, the latest emission legislation (Euro 7) proposes more stringent limits and testing conditions for vehicle emissions. To meet these limits, the automotive industry is actively developing innovative exhaust emission-control technologies.

With the growing prevalence of electrification, internal combustion engines are subject to continuous variations in load and engine speed, including phases where the engine is switched off. The result is an operating condition characterized by successive cold starts. In this context, the challenge in coping with the emission limits is to minimize the light-off time and prevent fast light-out conditions during idling or city driving. This goal can be achieved by reducing heat losses and thermal inertia, and suitably exploiting electrically heated solutions to maintain the catalyst inlet temperature at the desired level. In addition, issues related to mechanical durability must be considered, to allow the long-term life of the catalyst during continuous heat-up and cool-down cycles under severe flow conditions.

This paper aims to contribute to the development of an efficient after-treatment system, designed specifically for passenger cars, and to provide insights into the optimization of the catalyst design. This study employed advanced computational fluid dynamics (CFD) simulations to investigate the performance of a catalyst under a real driving emission cycle (RDE). A close-coupled configuration in a turbocharged gasoline engine was investigated. A detailed analysis of the external region of the substrate, which is critical because the temperatures are lower due to the heat transfer towards the environment, allows the identification of a suitable configuration. Flow conditions with post-turbo swirled flow along with the actuation of the wastegate valve were considered, and their impact on the pollutant abatement efficiency of the catalyst was evaluated.

A CFD framework has been implemented based on the open-source OpenFOAM code, modeling the complex phenomena of heat and mass transfer and catalytic reactions occurring in the substrate. Measured data of pollutant emissions and gas temperatures have allowed the validation of the CFD predictions and the optimization of the after-treatment system to limit the heat losses and reduce the pollutants emitted in the atmosphere during a real driving emission test cycle.
Evaluation of Engine and Aftertreatment Concepts for Proposed Tier 5 off-Road Emission Standards
Authors: Fnu Dhanraj , Joshi Satyum , Koehler Erik , Franke Michael , Tomazic Dean
Published: April 2024

The global push towards reducing green-house gas and criteria pollutant emissions is leading to tighter emission standards for heavy-duty engines. Among the most stringent of these standards are the California Air Resource Board (CARB) 2024+ HD Omnibus regulations adopted by the agency in August 2020. The CARB 2024+ HD Omnibus regulations require up to 90% reduction in NOx emissions along with updated compliance testing methods for on-road heavy-duty engines. Subsequently, the agency announced development of new Tier 5 standards for off-road engines in November 2021. The Tier 5 standards aim to reduce NOx/PM emissions by 90%/75% respectively from Tier 4 final levels, along with introduction of greenhouse gas emission standards for CO2/CH4/N2O/NH3. Furthermore, CARB is also considering similar updates on compliance testing as those implemented in 2024+ HD Omnibus regulations including, low-load cycle, idle emissions and 3-bin moving average in-use testing. While multiple technologies have already been developed for on-road engines to meet the 2024+ HD Omnibus regulations, they cannot be directly applied to off-road engines due to unique requirements of diverse machine applications, high durability, high reliability, packaging for visibility/turning radius, initial machine cost, transient response, and high low-end torque. A model-based approach is therefore necessary to evaluate tradeoffs in multiple engine and aftertreatment technology concepts to develop a modular, scalable, robust and cost-effective solution for meeting the proposed Tier 5 standards.

Following the extensive evaluations previously conducted by the authors on technology solutions for meeting on-road 2024+ HD Omnibus emission regulation, a model-based approach using GT-SUITE has been presented in this study to evaluate engine and aftertreatment technology packages for meeting the proposed off-road Tier 5 emission regulation. A validated engine and aftertreatment model of the baseline 228kW diesel engine was modified to investigate multiple advanced engine and aftertreatment technologies such as downspeeding, exhaust gas recirculation (EGR) pump, electric turbocharger (E-Turbo), variable geometry turbochargers (VGT), exhaust variable valve timing (Ex-VVT), dual urea dosing, closed couple catalysts and electric heater (EH) on off-road engine duty cycles. The technology packages were compared over Non-Road Transient Cycle (NRTC) cycle that is currently used for off-road engine certification. Key focus was placed on reducing engine out NOx during cold start, aftertreatment warmup, aftertreatment temperature-hold and NOx/CO2 tradeoff. Additional cycles that were investigated included a CARB recommended low load cycle, extended idle and a real-world challenge cycle for in-use compliance assessment.
Kinetic Model Development for Selective Catalytic Converter Integrated Particulate Filters
Authors: Kannan Rajesh , Paramadhayalan Thiyagarajan , Mital Rahul , Gustafson Erik , Edwards David
Published: April 2024

To meet the stringent NOx and particulate emissions requirements of Euro 6 and China 6 standard, Selective Catalyst Reduction (SCR) catalyst integrated with wall flow particulate filter (SCR-DPF) has been found to be an effective solution for the exhaust aftertreatment systems of diesel engines. NOx is reduced by ammonia generated from urea injection while the filter effectively traps and burns the particulate matter periodically in a process called regeneration. The engine control unit (ECU) effectively manages urea injection quantity, timing and soot burning frequency for the stable functioning of the SCR-DPF without impacting drivability. To control the NOx reduction and particulate regeneration process, the control unit uses lookup tables generated from extensive hardware testing to get the current soot load and NOx slip information of SCR-DPF as a function of main exhaust state variables.

In the current work, engine dynamometer tests were conducted on a SCR-DPF at different operating conditions covering typical vehicle running conditions. The oxygen assisted and NO2 assisted soot burning efficiency of the SCR-DPF was measured with and without urea injection at different soot loads. The impact of ammonia on soot burning at different engine operating conditions was studied. Using the test data, a physics based 1-D reaction model was developed with NOx reduction and soot oxidation reactions. The detailed SCR chemistry includes reactions for ammonia adsorption/desorption, NO oxidation, NH3 oxidation, standard/fast/slow NOx reduction and N2O formation. The soot burning reaction kinetics is described by the oxidation of soot with NOx. The NOx reduction and soot regeneration efficiency predictions of the model were validated with test values measured at engine dynamometer conditions under various exhaust flow rate, temperature, and soot load conditions. This 1-D kinetic model can be applied to generate calibration look up tables for the SCR-DPF control system in the vehicle to identify the right soot burning protocol to achieve the target regeneration efficiency. Few of the other areas where the model can be applied are, exhaust aftertreatment (EAT) architectural evaluation, converter sizing, wash coat loading studies, urea injection strategy development and heater element controls optimizations. Compared to the conventional hardware test-based approach, this model-based virtual approach uses less test data thus resulting in faster product development cycle and reduces the testing in engine dynamometer and vehicles.
Terrain Streaming for Real-Time Vehicle Dynamics
Authors: Brudnak Mark
Published: April 2024

This paper describes an approach to integrating high-fidelity vehicle dynamics with a high-fidelity gaming engine, specifically with respect to terrain. The work is motivated by the experimental need to have both high-fidelity visual content with high-fidelity vehicle dynamics to drive a motion base simulator. To utilize a single source of terrain information, the problem requires the just-in-time sharing of terrain content between the gaming engine and the dynamics model. The solution is implemented as a client-server with the gaming engine acting as a stateless server and the dynamics acting as the client. The client is designed to actively maintain a locally cashed terrain grid around the vehicle and actively refresh it by polling the server in an on-demand mode of operation. The paper discusses the overall architecture, the protocol, the server, and the client designs. A practical implementation is described and shown to effectively function in real-time. The benefit of the server architecture is demonstrated through an automated scanning client implemented in Python. Design decisions are discussed throughout.
Advancements in Combustion Modeling and Simulation for an Innovative Homogenous Reactivity-Controlled Compression Ignition (hRCCI) Concept
Authors: Sundaram Pravin Kumar , Grundl Larissa Michaela , Trapp Christian
Published: April 2024

The global imperative to develop clean energy solutions has redirected research efforts towards highly efficient combustion engines with ultra-low emissions. This has prompted investigations into alternative combustion concepts, including Low Temperature Combustion (LTC), utilizing environmentally friendly fuels. Within the scope of our research project, we are primarily focused on the development of an innovative combustion concept known as Homogeneous Reactivity-Controlled Compression Ignition (hRCCI), which employs renewable fuels such as ethanol and 1-octanol for a serial hybrid powertrain. The lack of predictive simulations for this concept presents a significant challenge in optimizing the engine's operation.

Most of the 1D system simulation models use a non-predictive combustion model for combustion simulations. Due to the dependence on auto-ignition chemistry, a chemistry based hRCCI combustion model for real time computation has been proposed with this work. Based on the thermal and chemistry data, a tabulated chemistry was generated using Ansys Chemkin. This table is further processed in Matlab- Simulink to predict the combustion in the proposed engine configuration. This helps in the simulation of combustion in real time and predicts the combustion profile before the start of combustion. This is one of the first steps in realizing multizone combustion modelling in 1D simulation to accurately predict the combustion.

Multidimensional computational fluid dynamics (CFD) simulation helps to refine the combustion process and provides a deeper understanding of the processes in the combustion chamber. Unsteady Reynolds averaged Navier-Stokes turbulence (URANS) simulations with detailed chemistry were previously conducted. For further insight into the hRCCI combustion process, a 2D CFD model of the combustion chamber with Large Eddy Simulation (LES), Partially averaged Navier-Stokes (PANS) and URANS turbulence model is developed using AVL FIRE M. The LES and PANS turbulence method consider the temperature variance due to the flow. This allows the precise depiction of the influence of turbulence on the combustion parameters like ignition delay, pressure rise, rate of heat release etc., and for the hRCCI concept it was found, that the flow field lead to a different temperature distribution compared to the URANS simulation and thus have an influence on the start of combustion.
Eddy-Resolving Simulation of Conjugate Heat Transfer in a Test Specimen pertinent to Cooling Channels in IC Engines
Authors: Kutej Lukas , Klink Artur , Wegt Sebastian , Reitz Ruediger , Jakirlic Suad
Published: April 2024

The conjugate heat transfer, which effectively integrates the heat conduction within the solid metal block of the so-called Water Spider Geometry (WSG) configuration and the fluid domain within it, is computationally investigated in the present work, allowing an accurate representation of the temperature conditions at the solid-fluid interface. The WSG configuration represents a specially configured tube geometry that effectively reproduces the flow behavior observed in cooling channels associated with Internal Combustion (IC) engines. The inherent high flow unsteadiness potential of the WSG flow configuration, resulting from the complex flow guidance involving phenomena such as flow impingement, bifurcation, multiple deflections and flow confluence, requires the application of a model capable of capturing turbulence fluctuations. Consequently, the solutions for the coupled flow and thermal fields are obtained by applying a novel eddy-resolving method employing the sub-scale model for solving the equations governing the unresolved residual turbulence quantities. For the latter, a four-equation model is used that solves, in addition to the equations governing the subscale kinetic energy of turbulence and its dissipation rate, the equation describing the dynamics of the normal-to-wall turbulence intensity component. The results obtained for two distinct fluid flow rates and a heat transfer rate, corresponding closely to those encountered in IC-related cooling channels, are discussed along with the reference flow data obtained with high-resolution LES and scale-resolved Sensitized RANS methods and the experimentally determined wall temperatures.
Effect of Baffle Height on the in-Cylinder Air-Fuel Mixture Preparation in a Gasoline Direct Injection Engine – A Computational Fluid Dynamics Analysis
Authors: V Vishal , Mallikarjuna J M
Published: April 2024

In-cylinder fluid dynamics enhance performance and emission characteristics in internal combustion (IC) engines. Techniques such as helical ports, valve shrouding, masking, and modifications to piston profiles or vanes in ports are employed to achieve the desired in-cylinder flows in these engines. However, due to space constraints, modifications to the cylinder head are typically minimal. The literature suggests that introducing baffles into the combustion chamber of an IC engine can enhance in-cylinder flows, air-fuel mixing, and, subsequently, stratification. Studies have indicated that the height of the baffles plays a significant role in determining the level of improvement in in-cylinder flow and air-fuel mixing. Therefore, this study employs Computational fluid dynamics (CFD) analysis to investigate the impact of baffle height on in-cylinder flow and air-fuel mixing in a four-stroke, four-valve, spray-guided gasoline direct injection (GDI) engine. The maximum allowable baffle height is limited to the minimum distance between the piston and cylinder head surface when the piston is at the top dead centre (TDC). The analysis involves varying the baffle height from 1 mm to 3 mm. Additionally, a new discretisation scheme is introduced to assess the mixing level within the combustion chamber. The results indicate a significant influence of baffle height on in-cylinder flows. Notably, a 1 mm baffle height yields a flow and mixing pattern similar to that of the base engine without baffles. As the baffle height increases, the in-cylinder flows are altered, leading to the formation of multiple vortices due to the presence of baffles. Furthermore, an increase in baffle height enhances mixture stratification, confining more fuel toward the spark plug location.
Study of Dimethyl Ether Fuel Spray Characteristics and Injection Profile
Authors: Cong Binghao , Leblanc Simon , Yu Xiao , Zheng Ming
Published: April 2024

The majority of transportation systems have continued to be powered by the internal combustion engine and fossil fuels. Heavy-duty applications especially are reliant on diesel engines for their high brake efficiency, power density, and robustness. Although engineering developments have advanced engines towards significantly fewer emissions and higher efficiency, the use of fossil-derived diesel as fuel sets a fundamental threshold in the achievable total net carbon reduction. Dimethyl ether can be produced from various renewable feedstocks and has a high chemical reactivity making it suitable for heavy-duty applications, namely compression ignition direct injection engines. Literature shows the successful use of DME fuels in diesel engines without significant hardware modifications. The lower energy density of DME calls for adjustments in injection parameters (such as injection pressure and duration) or modifications to the injector geometry to align with the energy levels found in diesel fuels. However, detailed direct comparisons between diesel and DME fuel injection characteristics over a wide testing range is lacking.

This study investigates the injection characteristics of DME and diesel fuels in a common rail fuel injection system using the Bosch tube method. It is demonstrated that this method can be effectively applied to measure DME fuel injection characteristics, albeit with some limitations in predicting injector closing delay. The research emphasizes the presence of hydraulic delay, resulting in a ratio of actual to commanded injection duration for DME between 1.5 to 2 under the testing conditions. The study finds that mass-based injection quantities for diesel and DME fuels are quite similar at matching conditions, although the lower heating value of DME results in lower energy-based injection quantities and thus fuel injection scheduling need to be adapted to compensate that. Furthermore, the paper offers valuable insights and suggestions for those considering the modification of diesel-operated engines into DME-operated engines.
WITHDRAWN Virtual validation of water drip test for non-sealed automotive electronic products towards Ingress Protection requirements
Authors: Kumar Vinay , Viswanathan Swaminathan , Dhanasekaran Prem
Published: April 2024

Modern automobiles are dependent on complex networks of electronic sensors and controls for efficient and safe operation. These electronic modules are tested for stringent environmental load conditions where product validation consists of one or a combination of loads such as Vibration, Mechanical Shock, Temperature, Water, Humidity, Dust, Chemicals, and Radiation. Exposure of electronics to water leads to many harmful effects resulting in the failure of electronic systems. Previously published technical paper [1] SAE 2023-01-0157 described a methodology to estimate risk in a humid environment, where water is dispersed in air as a gas phase. The present paper extends the scope of virtual validation using Computational Fluid Dynamics (CFD) simulation tools to an environment with water in the liquid phase.

In this paper, a non-sealed automotive electronic module subjected to a water drip test is evaluated using the CFD model. A transient 3D multiphase simulation is performed using the Volume of Fluid method (VOF) to simulate water droplets falling on a module mounted as per the test set-up described in ISO 20653. The study focuses on issues related to the simulation of the IPx2 test set-up at a ‘product level’. Computational challenges of performing such assessment are described with emphasis on rapid evaluation of design concepts along with necessary simplification in model and test set-up. ISO standard does not describe the pass/fail criterion objectively hence practical considerations of evaluation criterion are briefly outlined.
Lyapunov Exponent Based Stability Analysis for a High-Dimensional Nonlinear Vehicle System Under Extreme Condition
Authors: Lian Renzong , Li Zhiheng
Published: April 2024

The vehicle stability assessment system is an indispensable component to ensure driving safety and enhance vehicle motion control, whether for automated or human-driven vehicles, especially in extreme operating conditions. However, the existing stability assessment methods tend to be conservative and often ignore the coupled longitudinal and lateral dynamics, as well as the nonlinear characteristics of tires. To evaluate the vehicle stability accurately and quickly, an 8-degree-of-freedom (DOF) vehicle dynamic model is constructed first, considering the nonlinear characteristics of tires through a physics-based approach. Subsequently, the vehicle and environment parameters are auto-tuned using Bayesian optimization with field test data. Based on the adjusted vehicle model, a Lyapunov exponent (LE) based vehicle stability analysis method is proposed to quantitatively assess the stability of the vehicle state and determine the corresponding stability boundary. Within this framework, 3-dimensional LEs, encompassing lateral velocity, yaw rate, and roll rate, are employed to comprehensively evaluate the stability of vehicle state. This approach ensures evaluation accuracy while reducing computational complexity. Experimental results demonstrate that the proposed method is validated by field test data from a typical scenario on the ice-snow road, i.e., evasive maneuver test, through the values of 3-dimensional LEs. Negative LE values indicate that the vehicle states fall within the stability boundary, while the magnitude of LE represents the degree of stability.
Real-time Multi-Layer Predictive Energy Management for a Plug-in Hybrid Vehicle based on Horizon and Navigation Data
Authors: Liu Xuewu , Deng Yunfei , Xiong Jie , Wu Xiaojun , Srivastava Vivek , Pan Wang , Schaub Joschka , Muthyala Paul , Sun Jianqiang
Published: April 2024

Plug-In Hybrid Vehicles (PHEV) have been of significant importance recently to comply with future CO2 and pollutant emissions limit. However, performance of these vehicles is closely related to the energy management strategy (EMS) used to ensure minimum fuel consumption and maximize electric driving range. While conventional EMS concepts are developed to operate in wide range of scenarios, this approach could potentially compromise the fuel consumption benefit due to the omission of route and traffic information. With the advancements in the availability of real-time traffic, navigation and driving route information, the EMS can be further optimized to extract the complete potential of a PHEV. In this context, this paper presents application of predictive energy management (PEM) functionalities combined with information such as live traffic data to reduce the fuel consumption for a P1/P3 configuration PHEV vehicle. The proposed PEM uses on-board navigation and E-horizon data based on Advanced Driver Assistance Systems Interface Specifications (ADASIS). A multi-layer optimization approach is implemented across different prediction horizons. In the long horizon, Dynamic Programming (DP) calculates the optimal battery SoC (State of Charge) trajectory for the entire driving route. The search domain and discretization step of DP are optimized to ensure real-time capability. Based on this target SoC, Pontryagin’s Minimum Principle (PMP) is used in the short to medium horizon to calculate an Equivalence Factor (EF) that defines the optimal distribution between fuel and electrical energy. For the low-level EMS, Equivalent Consumption Minimum strategy (ECMS) is used that computes the torque split, gear ratio and engine on/off decision based on the EF from PMP. The fuel consumption savings for the developed PEM functions are investigated in comparison to conventional rule-based (RB) EMS for different real-world use-cases.