bluuebunny/crossref_metadata_2025 huggingface dataset:
Expanding the Use of Vehicle Specific Power in Analysis of Platoon Performance
Authors: Bentley John , Stegner Evan , Bevly David M. , Hoffman Mark
Published: April 2024

Platooning is a coordinated driving strategy by which following trucks are placed into the wake of leading vehicles. Doing this leads to two primary benefits. First, the vehicles following are shielded from aerodynamic drag by a “pulling” effect. Secondly, by placing vehicles behind the leading truck, the leading vehicles experience a “pushing” effect. The reduction in aerodynamic drag leads to reduced fuel usage and, consequently, reduced greenhouse gas emissions. To maximize these effects, the inter-vehicle distance, or headway, needs to be minimized. In current platooning strategy iterations, Coordinated Adaptive Cruise Control (CACC) is used to maintain close following distances. Many of these strategies utilize the fuel rate signal as a controller cost function parameter. By using fuel rate, current control strategies have limited applicability to non-conventional powertrains.

Vehicle Specific Power (VSP) has shown promise as a metric by which the performance of such controllers can be measured. This study uses VSP to characterize the platooning performance of each vehicle participating in multiple testing campaigns. The data set includes a variety of platoon headway setpoints, two and four-truck platoon configurations, two different testing locations, and experimental results utilizing vastly different platooning control strategies. This effort validates the use of VSP as a platooning characterization metric through the inclusion of a larger data set than prior studies. Additionally, the current work illustrates the broad applicability of VSP as a platooning assessment metric by utilizing multiple vehicles operating in a variety of configurations.

VSP also has the potential to serve as a powertrain-independent replacement for the use of fuel rate in a CACC predictive control cost function. In exploration of this idea, several vehicles’ fuel rate and fuel consumption were compared to VSP results. VSP and fuel consumption are shown to possess a direct relationship; but a stronger correlation is found between fuel consumed and the sum of positive VSP. Recommendations for the adaptation of VSP to platoon performance and control are made.
The New Toyota 2.4L L4 Turbo Engine with 8AT and 1-Motor Hybrid Electric Powertrains for Midsize Pickup Trucks
Authors: Endo Motoshiro , Bridge Alistair , Ikeda Akihiro , Miyamoto Koichi , Miyazaki Terufumi , Hosoda Fuminori , Herring Craig , Wallace James J. , Hu Mu
Published: April 2024

Toyota has developed a new 2.4L L4 turbo (2.4L-T) engine with 8AT and 1-motor hybrid electric powertrains for midsize pickup trucks. The aim of these powertrains is to fulfill both strict fuel economy and emission regulations toward “Carbon Neutrality”, while exceeding customer expectations. The new 2.4L L4 turbocharged gasoline engine complies with severe Tier3 Bin30/LEVIII SULEV30 emission regulations for body-on-frame midsize pickup trucks improving both thermal efficiency and maximum torque. This engine is matched with a newly developed 8-speed automatic transmission with wide range and close step gear ratios and extended lock-up range to fulfill three trade-off performances: powerful driving, NVH and fuel economy. In addition, a 1-motor hybrid electric version is developed with a motor generator and disconnect clutch between the engine and transmission. This hybrid architecture provides EV driving, which enhances the NVH and fuel economy, and provides additional acceleration with motor assist. Moreover, this hybrid electric system can meet customers’ “overlanding” electric power usage expectations. These performances will help exceed customer expectations for various pickup truck uses such as on-road, off-road and towing situations.
Ultra-Downsizing of ICEs Based on True Atkinson Cycle Implementations. Thermodynamic Analysis and Comparison on the Indicated Fuel Conversion Efficiency of Atkinson and Classical ICE Cycles
Authors: Gheorghiu Victor
Published: April 2024

Ultra-Downsizing (UD) was introduced as an even higher level of downsizing for Internal Combustion Engines ICEs, see [2] SAE 2015-01-1252.

The introduction of Ultra Downsizing (UD) aims to enhance the power, efficiency, and sustainability of ICEs while maintaining the thermal and mechanical strain within acceptable limits. The following approaches are utilized:
1
True Atkinson Cycles are implemented utilizing an asymmetrical crank mechanism called Variable Compression and Stroke Ratios (VCSR). This mechanism allows for extended expansion stroke and continuous adjustment of the Volumetric Compression Ratio (VCR).

2
Unrestricted two or more stage high-pressure turbocharging and intensive intercooling: This setup enables more complete filling of the cylinder and reduces the compression work on the piston, resulting in higher specific power and efficiency.

3
The new Load Control (LC) approach is based to continuous VCR adjustment. By adjusting the VCR without resorting to excessive throttling or external Exhaust Gas Recirculation (EGR), a stoichiometric Air Fuel Ratio (AFR) can be maintained. This facilitates easier exhaust gas aftertreatment using a three-way catalyst.

4
Fuel Flexibility: The continuous VCR adaptation capability enables the engine to operate in multi-fuel mode. In addition to gasoline or diesel, the engine can also run on alternative fuels like pure hydrogen (H2) or H2 blended with gases like CNG, Biogas, e-fuels, or even ammonia (NH3). This versatility allows for reduced carbon emissions and increased sustainability.

By combining these approaches, the UD concept aims to achieve higher power output, improved efficiency, and reduced environmental impact in ICEs, all while ensuring the durability and strength of engine components remain within acceptable limits.

The thermodynamic analysis is done separately for ideal and real cycles in order to determine the Indicated Fuel Conversion Efficiency (IFCE), formulaically (for ideal cycles) and quantitatively (for real cycles).

AVL BOOST © is used to simulate the real cycles (within cylinder and turbocharger) and MATLAB © to process the simulation results.
Numerical Study on the Combustion Characteristics of an Ammonia/Hydrogen Engine with Active Prechamber Ignition
Authors: Ma Zhe , Wang Chenxu , Deng Jun , Shang Quanbo , Tang Yongjian , Chen Haie , Huang Yi , Li Liguang
Published: April 2024

Both ammonia and hydrogen, as zero-carbon fuels for internal combustion engines, are received growing attention. However, ammonia faces a challenge of low flame propagation velocity. Through injecting hydrogen into active pre-chamber, its jet flame ignition can accelerate the flame propagation velocity of ammonia. The influence of different pre-chamber structures on engine combustion characteristics is significant. In this paper, numerical studies were conducted to assess the impact of various pre-chamber structures and hydrogen injection strategy on the combustion characteristics of ammonia/hydrogen engines while maintaining the equivalent ratio of 1.0. The results indicate that the jet angle significantly affects the position of jet flame and the followed main combustion. The in-cylinder combustion pressure peaks at jet angle of 150°. Meanwhile, the combustion duration of 150° is shortened by 74.3% compared with that of 60°. When the jet angle is 160°, the flame jet is positioned too far up into the slit between the cylinder head and the piston, resulting in a deteriorated combustion. Among the different numbers of pre-chamber jets, the combustion characteristics of the structure with 6 jets is the best. The diameter of the pre-chamber jet has less influence on the combustion. The effect of hydrogen injection on combustion was studied by employing the optimized pre-chamber structure. Misfire occurs when the hydrogen injection timing is -30 °CA ATDC. Advancing the injection timing can avoid the misfire, and is favorable for hydrogen to form the mixture, thus accelerating the combustion speed in the main combustion chamber. When the hydrogen ratio increases from 5.0% to 20.0%, the combustion duration is shortened from 19.2°CA to 5.1°CA.
Simulation Study of Sparked-Spray Induced Combustion at Ultra-Lean Conditions in a GDI Engine
Authors: Li Minglong , Long Quan , Yu Wangchao , Hu Zongjie , Yin Yong , Qin Xiongjie , Li Liguang
Published: April 2024

Ultra-lean combustion of GDI engine could achieve higher thermal efficiency and lower NOx emissions, but it also faces challenges such as ignition difficulties and low-speed flame propagation. In this paper, the sparked-spray is proposed as a novel ignition method, which employs the spark to ignite the fuel spray by the cooperative timing control of in-cylinder fuel injection and spark ignition and form a jet flame. Then the jet flame fronts propagate in the ultra-lean premixed mixture in the cylinder. This combustion mode is named Sparked-Spray Induced Combustion (SSIC) in this paper.

Based on a 3-cylinder 1.0L GDI engine, a 3D simulation model is established in the CONVERGE to study the effects of ignition strategy, compression ratio, and injection timing on SSIC with a global equivalence ratio of 0.50. The results show it is easier to form the jet flame when sparking at the spray front because the fuel has better atomization and lower turbulent kinetic energy at the spray front. The jet flame will be stronger if the ignition position is further from the injector, leading to shortened combustion duration and lower CO, Soot and HC emissions, but higher NOx emissions due to the increase of combustion temperature. With the increase of compression ratio, flame propagation speed is faster, thermal efficiency is higher (46.6% at compression ratio 14), and the emissions of CO, Soot and HC are decreased significantly, but NOx emissions are increased. At the compression ratio of 14, with the advance of injection timing, the thermal efficiency increased firstly and then decreased (47.3% at injection timing -30°CA ATDC), while HC, CO, Soot and NOX emissions all decreased.
Demonstration of Low Criteria Pollutant and Greenhouse Gas Emissions: Synergizing Vehicle Emission Reduction Technology and Lower Carbon Fuels
Authors: Storch Michael , Singh Ripudaman , Haubold Sven , Voice Alexander
Published: April 2024

This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF).

An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C. Several EN228 compliant fuels, including lower-carbon fuel candidate, were tested. Fuels were formulated representing the distribution of volatility, C9 and higher aromatics (A9+), and C11 and higher aromatics (A11+) currently in the European market.

The results show that with ULE technology, a significant reduction in tailpipe emissions is achievable across various test cycles and conditions. It was found that fuel property effects on tailpipe emissions are mitigated by the ULE test vehicle. However, the engine-out total hydrocarbon (THC) and particle number (PN) emission showed sensitivity to fuel formulation. Fuel mid-distillation range was a good general predictor of engine-out THC emissions. Engine-out PN emissions were not consistently correlated with any fuel properties. However, Yield Sooting Index (YSI) in combination with back-end volatility was correlated with PN emissions on two of three test cycles on this vehicle.
Reference Velocity Estimation with Variable Gain Based on Powertrain Dynamics for Production Hybrid Electric Vehicle
Authors: Li Huan , Liu Xuewu , Wang Jinhang , Chen Lihua , Xu Yin , Wu Meng
Published: April 2024

Reference velocity (i.e. the absolute velocity of vehicle center of gravity) is a key parameter for vehicle stability control functions as well as for the powertrain control functions of hybrid electric vehicle (HEV). Most reference velocity estimation methods employ the vehicle kinematic and tire dynamic equations to construct high order linear or nonlinear model with a set of parameters and sensor measurements. When using those models, delicate algorithm should be designed to prevent the estimates from deviating along with the increase of nonlinearity, modeling error and noise that introduced by high order, parameter approximation, and sensor measurements, respectively. Alternatively, to improve the function robustness and calibration convenience, a straightforward online estimation method is developed in the paper by using a second-order powertrain dynamic model that only need a small set of vehicle parameters and sensor values. First, the HEV powertrain dynamic model is established for the vehicle longitudinal velocity estimation. Second, a classic Luenberger observer with variable estimation gains are designed. Third, the variable estimation gains are scheduled based on the vehicular operational conditions to determine whether the estimates need to be dominated by the dynamic model or by the measurements in different condition. Then the algorithm is integrated into the vehicle control unit (VCU) of a mass production HEV, which is a powertrain supervisory controller that possesses all the control inputs and measurements signals needed by the observer. Finally, the estimation accuracy is verified by experiments on both high- and low-μ (-adhesion) road, such as the snow surface, ice surface, and urban concrete pavement, etc. Due to the low order and minor parameters and measurements needed, as well as the variable estimation gain scheduled with operational conditions, the algorithm robustness and calibration convenience are guaranteed.
Simple Hybrid Electric Vehicle Operating and Fuel Consumption Model
Authors: Phlips Patrick
Published: April 2024

An analytic first-order fuel consumption model is developed for FWD 2-motor HEV vehicles which on average achieve 36% EPA Combined efficiency. The premise of this paper is that this is primarily the result of new functionality specific to HEV. Detailed benchmarking data show that in such an HEV the engine not only provides traction power but simultaneously charges the battery. This combined operation of engine and electric powertrain is unique to HEV and is studied using their linear transfer functions. Charging by the engine enables extended electric driving at low traction power, which reduces engine running time and the associated overhead. The analysis predicts an engine duty cycle proportional to the traction power and inversely proportional to the engine output power: the electric driving is limited by the engine’s ability to deliver the required traction work. The model equations in terms of the major functional parameters predict engine running time fractions of 15% for the EPA urban Bag 2 test and 54% on the EPA Highway test, versus observed values of 15% and 51%. As the small HEV High Voltage battery provides little net charge over a trip, the fuel consumption is proportional to the sum of the net engine work and the reduced, proportional overhead. On low power regulatory cycles, the fuel consumption changes from ‘constant overhead’ in classical ICEV to ‘constant high efficiency’ in HEV. Cycle efficiencies of 37 and 36% are predicted for the urban Bag 2 and Highway tests for a generic vehicle.
V2X Communication Protocols to Enable EV Battery Capacity Measurement: A Review
Authors: Roy Apoorva , Siegel Jason , Bhagdikar Piyush , Gankov Stanislav , Rao Sandesh
Published: April 2024

The US EPA and the California Air Resources Board (CARB) require electric vehicle range to be determined according to the Society of Automotive Engineers (SAE) surface vehicle recommended practice J1634 - Battery Electric Vehicle Energy Consumption and Range Test Procedure. In the 2021 revision of the SAE J1634, the Short Multi-Cycle Test (SMCT) was introduced. The proposed testing protocol eases the chassis dynamometer test burden by performing a 2.1-hour drive cycle on the dynamometer, followed by discharging the remaining battery energy into a battery cycler to determine the Useable Battery Energy (UBE). Opting for a cycler-based discharge is financially advantageous due to the extended operating time required to fully deplete a 70-100kWh battery commonly found in Battery Electric Vehicles (BEVs). This paper provides a review of the communication protocols enabling V2X (Vehicle to X, where X can be grid, vehicle, building, etc.) power transfer and the tools required to initiate, control, and terminate the vehicle testing procedure as per SAE J1634. The primary focus is on the series of ISO 15118 standards for road vehicles - vehicle to grid communication interface and SAE J2847/2 (Surface vehicle standard for communication between plug-in vehicles and off-board DC chargers).
Fuel Cell Hybrid Electric Vehicle: Validated Fuel Cell and Battery Pack Model to Enhance Reliability in Performance Predictions
Authors: Bartolucci Lorenzo , Cennamo Edoardo , Cordiner Stefano , Donnini Marco , Grattarola Federico , Mulone Vincenzo
Published: April 2024

In the face of the pressing climate crisis, a pivotal shift towards sustainability is imperative, particularly in the transportation sector, which contributed to nearly 22% of global Greenhouse Gas emissions in 2021. In this context, diversifying energy sources becomes paramount to prevent the collapse of sustainable infrastructure and harness the advantages of various technologies, such as Fuel Cell (FC) Hybrid Electric Vehicles. These vehicles feature powertrains comprising hydrogen FC stacks and battery packs, offering extended mileage, swift refueling times, and rapid dynamic responses. However, realizing these benefits hinges upon the adoption of a rigorously validated simulation platform capable of accurately forecasting vehicle performance across diverse design configurations and efficient Energy Management Strategies. Our study introduces a comprehensive microcar hybrid prototype model, encompassing all subsystems and auxiliaries. This model incorporates a validated FC stack Digital Twin, alongside an experimentally characterized Li-Ion Battery Pack, thus faithfully representing the real prototype. Moreover, the integration of this model has proven indispensable for design optimization, enabling precise performance estimation across various powertrain configurations. After the analysis of the experimental Pulse Discharge test and the calibration of the battery equivalent circuit with three RC branches, we comprehensively examined both single (2-kW) and parallel (4-kW) architectures, utilizing two FC stacks, on a reference driving cycle. Notably, the combination of two parallel stacks emerged as the most promising, yielding a 6% increase in estimated range. Our findings underscore the significance of this innovative approach in advancing sustainable transportation solutions.
Performance Comparison between Different Battery Architectures with Cell-to-Cell Variations
Authors: Patil Chinmaya , Cheng Ye
Published: April 2024

A 300 mile-range automotive battery pack is comprised of many individual cells connected in series/parallel to make up the required voltage, energy, and power. The cell groupings can take the form of parallel strings of series cell groups (S-P), series string of parallel cell groups (P-S), or a hybrid of the two. Though the different battery configurations deliver identical output voltage and energy, they exhibit varying cell level behaviors due to differing electrical structure, particularly when cell imbalance occurs. In this work, we explore the relative merits of various cell grouping configurations using a model-based approach. The emphasis of the study is to evaluate the impact of electrical variation between cell-to-cell, originating from cell manufacturing process variation, battery assembly (laser tab bonding) process variation or from normal operation, on the performance of the battery pack. A first-order equivalent circuit model is used to represent a lithium-ion cell. A model of the battery system with Nm modules of Ns cells in series and Np cells in parallel is developed and used to analyze the voltage and state-of-charge behavior of the system with various cell grouping configurations for a specified duty cycle. The imbalances between cell-to-cell voltage and currents are used as metrics for comparing different battery architectures. Using a low voltage battery system (<50V, 5 kWh nominal) as a case study, the simulation results indicate that the S-P cell grouping architecture is significantly more robust to cell-to-cell variations than P-S cell grouping architecture. Further, when paired with typical battery management system, the ability to diagnose a single cell malfunction (for example, faulty cell, poor tab weld, inadequate thermal management) is demonstrably higher for the S-P cell grouping architecture than the corresponding P-S system.
Stress Generation in Large Pouch Cells Under Cycling and Abuse Conditions
Authors: Swarts Andre , Salvi Swapnil Suryakant , Holmgreen Travis
Published: April 2024

Pouch cells are increasingly popular form factors for the construction of energy storage systems in electric vehicles of all classes. Knowledge of the stress generated by these higher capacity pouch cells is critical to properly design battery modules and packs for both normal and abnormal operation. Existing literature predominantly offers data on smaller pouch cells with capacities of less than 10 Ah, leaving a gap in our understanding of the behavior of these larger cells. This experimental study aimed to bridge this knowledge gap by measuring loads and stresses in constrained 65 Ah pouch cells under both cycling and abuse conditions. To capture the desired responses, a load cell was located within a robust fixture to measure cell stress in real time after the application of a preload of approximately 30 kilograms or 294 N, equivalent to a pressure of 0.063 bar, with a fixed displacement. The thermal distribution across the cells was monitored by thermocouples at multiple locations. Cell voltage and current measurements were done concurrently and all data was recorded continuously using a dedicated data acquisition system, supplemented by video imagery and post-test cell inspections and photographs. A cycling test was conducted over multiple charge-discharge cycles at a C/3 rate to monitor the stress development associated with cell ageing. The results revealed an increase in the maximum load from about 2000 N (0.43 bar) to more than 4,200 N (0.91 bar) after 34 cycles. Additionally, two short-circuit abuse tests were performed with an external hard short, simulating a potential failure scenario. The first test revealed peak loads of approximately 800 N (0.71 bar) before an unplanned electrical disconnection terminated the test. The peak load for the second test exceeded 4,200 N (0.91 bar) and before loss of the electrolyte.
Differential Flatness-Based Control of Switched Reluctance Motors
Authors: Niazi Yasaman , Gholaminejad Azadeh , Valencia Garcia Diego Fernando , Dhale Sumedh , Nahid-Mobarakeh Babak
Published: April 2024

This paper presents a Differential Flatness-Based Control (FBC) approach for the current control of Switched Reluctance Machines (SRMs), a potential candidate for the automotive industry. The main challenges in SRM control methods stem from motor nonlinearity. In electrical drives, FBC has been applied in doubly-fed induction generators, permanent magnet motors, and magnet-assisted synchronous reluctance motors. Among the few papers that have used FBC for SRM, this research distinguishes itself by addressing current control and considering both current and flux-linkage separately as a flat output, an approach not found in previous literature. The performance of the proposed controls is assessed in a three-phase 12/8 SRM against the conventional hysteresis current controller (HCC) and PI controller. Additionally, it is integrated into a torque-sharing function based on a maximum torque per ampere control strategy. This work uses the Integral Time Absolute Error (ITAE) criterion to compare different control methods. The current ITAE of FBC has been reduced by 50% compared to HCC and 41% compared to the PI controller. This controller is well-suited for transportation applications, mainly traction and propulsion in vehicles, due to its low loss and torque ripple compared to conventional controllers. Moreover, dynamic response to changes in load and dyno speed evidence the enhanced performance of the proposed technique.
Torque Ripple Cancellation to Reduce Electric Motor Noise for Electric Vehicles
Authors: He Song , Peddi Vinod , Chang Le
Published: April 2024

Electric motor whine is a major NVH source for electric vehicles. Traditional mitigation methods focus on e-motor hardware optimization, which requires long development cycles and may not be easily modified when the hardware is built. This paper presents a control- and software-based strategy to reduce the most dominant motor order of an IPM motor for General Motors’ Ultium electric propulsion system, using the patented active Torque Ripple Cancellation (TRC) technology with harmonic current injection. TRC improves motor NVH directly at the source level by targeting the torque ripple excitations, which are caused by the electromagnetic harmonic forces due to current ripples. Such field forces are actively compensated by superposition of a phase-shifted force of the same spatial order by using of appropriate current. A feedforward harmonic current generation module is developed, which allows the application of harmonic current commands to a motor control system with adjustable magnitude and phase. In the 3-phase, 8-pole AC machine with concentrated windings of this study, both 5th and 7th electric order harmonic currents are injected in the stationary reference frame to cancel the 6th electric order torque ripple in the synchronous reference frame, which corresponds to the most dominant 24th mechanical order. Test data confirm that TRC is highly effective in reducing the motor whine by 10+ dB over a wide range of motor torque. Loss study is also performed which shows TRC has a minimal impact on the motor efficiency. Overall, TRC offers a flexible NVH solution without hardware change and has minimum impact on motor performance or efficiency. The technology has been successfully implemented in GM’s Ultium electric propulsion systems.
Research on Voltage Control of Dual Motor Hybrid System
Authors: Jing Junchao , Sun Xudong , Liu Yiqiang , Huang Weishan
Published: April 2024

The paper introduces two methods for controlling motor voltage. One method requires the implementation of boost hardware, while the other allows for voltage control in battery failure mode without any additional hardware requirements. The boost voltage strategy for the hybrid system is based on managing boost modes, determining target voltages, and implementing PI control. The boost mode control includes different modes such as initial mode, normal mode, shutdown mode, and fault mode. Determining the boost target voltage involves regulating the boost converter with variable voltages depending on the operating states of the motor and generator. The second voltage control method without boost hardware is proposed in order to ensure that the vehicle can still function like a traditional car even under abnormal conditions of high-voltage battery failure in micro-mixing systems. In this mode, instead of conventional torque control, the generator operates in a voltage control mode where "voltage" becomes the controlled variable for its controller. The HCU controls the working mode switching of the motor and issues target voltage commands calibrated through actual tests. During system operation, the motor responds to these target voltages in real time. To evaluate the effectiveness of this voltage control strategy, tests were conducted on a sample car with a 2.0T displacement engine. The second voltage control strategy test results indicate that increasing the voltage from 250V to 450V significantly enhances power output at 6500rpm, resulting in a remarkable boost of approximately 117% (from 71 kW to 155 kW). This improvement leads to enhanced acceleration performance at high speeds and improved vehicle dynamics. The outcomes of the second voltage control strategy demonstrate that smoothly transitioning into voltage control mode and ensuring seamless operation when disconnecting the high voltage battery relay is achievable. This operational mode guarantees uninterrupted vehicle functionality even in cases of abnormality with the high-voltage battery. Additionally, serving as an auxiliary driving mode, it further strengthens the safety and robustness of the overall system.
Integrated Bracket for Rain Light Sensor/ADAS/Auto-Dimming IRVM with provision of mounting for Aesthetic Cover
Authors: Chandravanshi Priyansh , Parthiban Mohan , Bable Shubham , Dharmatti Girish
Published: April 2024

Plastic design is one of the upcoming fields of interest when it comes to weight optimization, sustainability, strength, and overall aesthetics of an automobile. What is often ignored is the amount of flexibility a plastic designer has, of integrating and packaging various components of an automobile into a single part and still make it an integral part of its complex aesthetics.

This paper highlights upon one such part that is being developed: An integrated bracket which packages ADAS camera, Rain Light Sensor, and an Auto-dimming IRVM. Apart from packaging the mentioned components, this bracket also has mounting provisions for an aesthetic cover (also referred to as beauty cover). The objective of this paper is to highlight the importance of integration of several parts into a single part for packaging multiple components that need to be placed in a close proximity with each other. This paper includes the demonstration of old design which consisted of multiple parts along with how we designed the integrated bracket and how it is better from the old design. This integrated bracket will be pasted with tapes and glue on the windshield of the automobile. The CAD tool used for designing is CATIA V5. While designing integrated bracket multiple criteria have to be considered from vehicle architecture point of view. The field of vision or FOV of the IRVM needs to qualify OEM standards which will vary for different OEMs. ADAS camera FOV also needs to be considered along with RLS sensor mounting requirements. All the above packaging constraints along with wiring harness routing makes integrated bracket an extremely complex plastic part.
A Switching Control Strategy for Multiple Heating Modes Based on the Integrated Thermal Management System of Electric Vehicles
Authors: Zhang Feng-Ting , Zhang Zai-Cheng , Liu Xiaoang , Shangguan Wen-Bin , Huang Yu , Li Guoqiang
Published: April 2024

To reduce the heating energy consumption of electric vehicles in winter, a switching control strategy for multiple heating modes formed by three heat sources, including air, motor waste heat, and positive temperature coefficient (PTC) heaters, is designed. Firstly, an integrated thermal management system (ITMS) simulation model for the heat pump air conditioning system, battery thermal management system, and motor thermal management system is established based on the AMESim software. Secondly, the influence of ambient temperature and motor outlet coolant temperature on the heating performance of three cabin heating modes is studied. Specifically, the three cabin heating modes include the pure motor waste heat source heat pump mode, the pure air-source heat pump mode, and the dual heat source heat pump mode with waste heat source and air source. Based on the analysis results, the opening and closing strategies for the three cabin heating modes are discussed. The optimum mode of using motor waste heat and PTC heater to heat the battery is further discussed. Based on the heating priority of the cabin and battery, as well as the maximum heating capacity of the heating modes including the air source, a switching control strategy for multiple heating modes is studied. The results show that compared to the traditional heating method of using the air-source heat pump for cabin heating and PTC heater for battery heating, the proposed control strategy in this paper can reduce the energy consumption of the studied electric vehicle by 18.3% if heating for 2 hours at the ambient temperature of -5 °C. This research provides an effective solution for heating the cabin and battery of electric vehicles in cold weather, significantly reducing energy consumption and extending the driving range.
A Method for Predicting Fatigue Life of Rubber Isolators at Power Spectral Density Load
Authors: Yao Qishui , Li Min , Zhang Licheng , Yue Zaiqin , Shangguan Wen-Bin
Published: April 2024

Rubber isolators are widely used under random vibrations. In order to predict their fatigue life, a study on the fatigue analysis methodology for rubber isolators is carried out in this paper. Firstly, taking a mount used for isolating air conditioning compressor vibrations as studying example, accelerations versus time of rubber isolator at both sides are acquired for a car under different running conditions. The acceleration in time domain is transformed to frequency domain using the Fourier transform, and the acceleration power spectral density (PSD) is the obtained. Using the PSD as input, fatigue test is carried for the rubber isolator in different temperature and constant humidity conditions. A finite element model of the rubber isolator using ABAQUS is established for estimating fatigue life, and model validity is verified through static characteristic testing. Dynamic responses of the rubber isolator at frequency domain are calculated if a unit load is applied. The estimated dynamic responses are then imported into Fe-safe for calculating fatigue analysis of the rubber isolator. The proposed methods in this paper are validated by comparing the calculated with the measured fatigue life. To enhance the fatigue life of the rubber isolator, structural optimization is carried out by optimizing main spring parameters. Fatigue life calculation of the optimized rubber isolator is then carried out and it is shown that the isolator meets design requirements. A frequency-domain calculation method of fatigue life proposed in this study can be used for assessing the fatigue life of rubber isolators under random vibration.
Tyre Slip Ratio Estimation Using Intelligent Tyre Concept
Authors: Li Bo , Gu TianLi , Bei Shaoyi , Guo Jinfei , Walid Daoud , Yi Aibin , Zhu Yunhai
Published: April 2024

Intelligent tyres can offer crucial insights into tyre dynamics, serving as a fundamental information source for vehicle state estimation and thereby enabling vehicular safety control. Among the numerous tyre parameters, slip ratio stands out as a direct influencer of vehicle motion characteristics. Accurate estimation of tyre slip ratio is essential for vehicle safety. Firstly, an analysis of the fundamental composition of tyres was conducted, and appropriate simplifications were applied to the tyre structure. Additionally, a finite element model of the tyre was constructed using ABAQUS software. To validate the reliability of the model, a real vehicle testing system was established, consisting of the experimental vehicle, data acquisition system, and supervisory computer. The reliability of the finite element model was confirmed by assessing the consistency of acceleration signals in three different directions of the tyre. Secondly, the variations in acceleration curves under different slip ratios were examined, revealing the most prominent features linearly correlated with slip ratios within the acceleration curves. These distinctive features were then extracted as inputs. Finally, a slip ratio prediction method based on the theory of backpropagation (BP) neural networks was proposed. A neural network prediction model was constructed with five distinctive features as inputs and slip ratio as the output. This model successfully achieved the estimation of tyre slip ratios. The result shows that the MAPE of the test set is 2.32%, and the prediction accuracy is high. It also reveals the fusion of intelligent tyre technology and neural network theory has great potential in predicting tyre slip ratio.
Dynamic Modeling of Quadrotor-Slung-Load System: A Model Based on the Quasi-Coordinates Approach
Authors: Zhang Hanwen , Duan Yupeng , Wu Jinglai , Zhang Yunqing
Published: April 2024

With the development of hardware and control theory, the application of quadcopters is constantly expanding. Quadcopters have emerged in many fields, including transportation, exploration, and object grabbing and placement. These application scenarios require accurate, stable, and rapid control, and a suitable dynamic model is one of the prerequisites. At present, many works are related to it, most of which are modeled using the Newton-Euler method. Some works have also adopted other methods, including the Lagrangian and Hamiltonian methods. This article proposes a new method that solves the Hamiltonian equation of a quadcopter expressed in quasi-coordinate. The external forces and motion of the body are expressed in the quasi-coordinate system of the body, and solved through the Hamiltonian equation. This method simplifies operations and improves computational efficiency. Additionally, a single pendulum is attached to the quadcopter to simulate application scenarios. For the additional single pendulum, it is treated as a particle and the degrees of freedom are constrained by a constraint equation, resulting in a differential algebraic equation. Different operating conditions were set, including stabilization and path flying with no load, and object swinging and path flying with load, for simulation. To achieve effective control, the PID method was adopted. The comparison of the calculation results with the Newton-Euler method proves that the computational complexity of this method is smaller. More specifically, the max improvement in the stabilization and path following are 7.69% and 6.83%, respectively.
Torque Vectoring for Lane-Changing Control during Steering Failures in Autonomous Commercial Vehicles
Authors: Lu Ao , Li Runfeng , Yinggang Xu , Nie Zexin , Li Peilin , Tian Guangyu
Published: April 2024

Lane changing is an essential action in commercial vehicles to prevent collisions. However, steering system malfunctions significantly escalate the risk of head-on collisions. With the advancement of intelligent chassis control technologies, some autonomous commercial vehicles are now equipped with a four-wheel independent braking system. This article develops a lane-changing control strategy during steering failures using torque vectoring through brake allocation. The boundaries of lane-changing capabilities under different speeds via brake allocation are also investigated, offering valuable insights for driving safety during emergency evasions when the steering system fails. Firstly, a dual-track vehicle dynamics model is established, considering the non-linearity of the tires. A quintic polynomial approach is employed for lane-changing trajectory planning. Secondly, a hierarchical controller is designed. The upper layer employs a three-stage cascaded proportional integral controller to determine the total yaw moment required for lane changing, considering the influence of lateral tire forces on brake allocation. The middle layer uses constraint optimization to manage braking force distribution among the four wheels. The lower layer's actuator generates brake torque through brake cylinder pressurization. Finally, the effectiveness and feasibility of the control strategy are validated using joint simulations on Matlab/Simulink and Trucksim over diverse longitudinal distances. Simulation results indicate that autonomous commercial vehicles can execute swift and safe lane changes at varying speeds during steering failures.
Experimental Study on Performance and Emissions of BS VI Complaint EFI Motorbike with Oxygenated Fuel Blends (E0, E10, E20 & M15)
Authors: Sahu Yaman , P Sakthivel , Sithananthan M , Maheshwari Mukul
Published: April 2024

Net-Zero emission ambitions coupled with availability of oxygenated fuels like ethanol encouraged the Government towards commercial implementation of fuels like E20. In this background, a study was taken up to assess the impact of alcohol blended fuels on performance and emission characteristics of a BS-VI complaint motorbike. A single cylinder, 113-cc spark ignition, ECU based electronic fuel injection motorbike was used for conducting tests. Pure gasoline (E0), 10% ethanol-gasoline (E10), 20% ethanol-gasoline (E20) and 15% methanol-gasoline (M15) blends meeting respective IS standards were used as test fuels. The oxygen content of E10, E20 and M15 fuels were 3.7%, 7.4% and 8.35% by weight respectively. Experiments were conducted following worldwide motorcycle test cycle (WMTC) as per AIS 137 standard and wide-open-throttle (WOT) test cycle, using chassis dynamometer.

The experimental results on WMTC tests indicated that the fuel consumption of the vehicle increased with increase in oxygen content of the test fuels. The maximum increase in fuel consumption was 6.40% with M15 fuel as compared to E0 fuel. CO2 emission decreased moderately with the use of oxygenated fuels due to lower carbon content. CO and THC emissions decreased with oxygenated fuels and E20 fuel resulted in lowest level compared to all other test fuels. NOx emission increased linearly with increase in oxygen content of the test fuels and M15 recorded the highest. Under WOT conditions, the carbon emissions (CO, THC) decreased significantly with oxygenated fuels, with increase in NOx emission due to better combustion. However, CO2 emission was higher for oxygenated fuels due to high fuel consumption to achieve desired power output under full load operation. Overall, the alcohol blends help to decrease the CO and THC emissions with slight penalty on fuel economy. Fine-tuning of ECU parameters specific to fuel, has potential to improve fuel economy while reducing emissions.
Optimization Methods to Enhance Performance of a Powertrain Mounting System at Key on and Key off
Authors: Lin Shuo , Yin Zhi-Hong , Jiang Yong-Feng , Song Yan-Ping , Shangguan Wen-Bin
Published: April 2024

To enhance the transient vibration performance of the vehicle at key on and key off, a method for optimizing mount parameters of a powertrain mounting system (PMS) is proposed. Uncertainties of mount parameters widely exist in a PMS, so a method for optimizing mount parameters of a PMS, which treats the mount parameters of a PMS as uncertain, is also proposed in this paper. Firstly, a 13 degrees of freedom (DOFs) model including car body with 3 DOFs, a PMS with 6 DOFs and unsprung mass with 4 DOFs is established, and the acceleration of the active side of mounts is calculated. An experiment is carried out to measure the accelerations located at active and passive sides of each mount and the accelerations of seat track. A comparison is made between the measured and estimated accelerations, and the proposed model is validated. Two optimization methods for the PMS are proposed based on the developed 13 DOFs model. One method treats mount parameters as deterministic variables, while another one treats them as interval variables. Vibration dose value (VDV) of longitudinal acceleration of a powertrain is defined as one of optimization objectives, and natural frequencies (NFs) placement and energy distributions of a powertrain in different directions are also defined as optimization objectives. The ranges of powertrain uncertain responses are obtained through the perturbation center difference method (PCDM) and are validated using the Monte Carlo method (MCM). The optimized upper and lower bounds of powertrain responses are also given. Finally, key on/off experiments with optimized mount parameters are carried out to validate the proposed methods.
Non-Destructive Parameterization of Lithium-Ion Batteries via Machine Learning with Simulated EIS Data
Authors: Alidadi Pasha , Schlösser Anton Emil Kaspar , Salek Farhad
Published: April 2024

Lithium-ion batteries are ubiquitous in modern energy storage applications, necessitating efficient methods for assessing their state and performance. This study explores a non-destructive approach to extract vital battery parameters using machine learning techniques applied to simulated Electrochemical Impedance Spectroscopy (EIS) data. EIS is a powerful diagnostic tool for batteries and provides a safe and repeatable alternative to the physical intrusion of battery dismantling, which could alter the batteries properties. The research focuses on the design and training of machine learning models for accurate prediction of battery parameters within the widely used P2D model. By leveraging the power of machine learning, this approach aims to accurately characterize the battery parameters using an electrochemical model as opposed to the less accurate equivalent circuit models, contributing to the reliability and longevity of lithium-ion batteries in diverse applications. The second part of this paper incorporates real-life experimental EIS data by utilizing an improved version of an open-source model called “Impedance Analyzer”. Multiple approaches have been explored and discussed to leverage machine learning algorithms to accurately estimate the battery parameters. The findings of this study pave the way for more robust, non-destructive battery assessment methods, crucial for advanced state of health prediction models of lithium-ion batteries.
Frontal Crash Oriented Robust Optimization of the Electric Bus Body Frame Considering Tolerance Design
Authors: Yang Xiujian , Liu Beizhen
Published: April 2024

For the design optimization of the electric bus body frame orienting frontal crash, considering the uncertainties that may affect the crashworthiness performance, a robust optimization scheme considering tolerance design is proposed, which maps the acceptable variations in objectives and feasibility into the parameter space, allowing for the analysis of robustness. Two contribution analysis methods, namely the entropy weight and TOPSIS method, along with the grey correlation calculations method, are adopted to screen all the design variables. Fifteen shape design variables with a relatively high impact are chosen for design optimization. A symmetric tolerance and interval model is used to depict the uncertainty associated with the 15 shape design variables of key components in the bus body frame to form an uncertainty optimization problem in the form of an interval, and a triple-objective robust optimization model is developed to optimize the shape design variables and tolerances simultaneously. The optimization problem is handled by the double-loop nested optimization algorithm, which combines the NSGA-III and the sequential quadratic programming (SQP) methods. The four sets of optimized crashworthiness midpoint values obtained from the optimization that meet the requirements of robustness and fluctuation range, as well as the tolerance evaluation coefficients, are analyzed, discussed, and compared with the measurements before optimization. The results demonstrate that the proposed robust optimization scheme, considering tolerances, effectively enhances the crashworthiness of the bus body frame under practical manufacturing conditions while ensuring the robustness of the optimization results.