bluuebunny/crossref_metadata_2025 huggingface dataset:
Upregulated lncRNA PRNT promotes progression and oxaliplatin resistance of colorectal cancer cells by regulating HIPK2 transcription
Authors: Li Sai-Nan , Yang Shan , Wang Hao-Qi , Hui Tian-Li , Cheng Meng , Zhang Xi , Li Bao-Kun , Wang Gui-Ying
Published: April 2024

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer and a significant cause of cancer-related mortality globally. Resistance to chemotherapy, especially during CRC treatment, leads to reduced effectiveness of drugs and poor patient outcomes. Long noncoding RNAs (lncRNAs) have been implicated in various pathophysiological processes of tumor cells, including chemotherapy resistance, yet the roles of many lncRNAs in CRC remain unclear.

AIM

To identify and analyze the lncRNAs involved in oxaliplatin resistance in CRC and to understand the underlying molecular mechanisms influencing this resistance.

METHODS

Gene Expression Omnibus datasets GSE42387 and GSE30011 were reanalyzed to identify lncRNAs and mRNAs associated with oxaliplatin resistance. Various bioinformatics tools were employed to elucidate molecular mechanisms. The expression levels of lncRNAs and mRNAs were assessed via quantitative reverse transcription-polymerase chain reaction. Functional assays, including MTT, wound healing, and Transwell, were conducted to investigate the functional implications of lncRNA alterations. Interactions between lncRNAs and transcription factors were examined using RIP and luciferase reporter assays, while Western blotting was used to confirm downstream pathways. Additionally, a xenograft mouse model was utilized to study the in vivo effects of lncRNAs on chemotherapy resistance.

RESULTS

LncRNA prion protein testis specific (PRNT) was found to be upregulated in oxaliplatin-resistant CRC cell lines and negatively correlated with homeodomain interacting protein kinase 2 (HIPK2) expression. PRNT was demonstrated to sponge transcription factor zinc finger protein 184 (ZNF184), which in turn could regulate HIPK2 expression. Altered expression of PRNT influenced CRC cell sensitivity to oxaliplatin, with overexpression leading to decreased sensitivity and decreased expression reducing resistance. Both RIP and luciferase reporter assays indicated that ZNF184 and HIPK2 are targets of PRNT. The PRNT/ZNF184/HIPK2 axis was implicated in promoting CRC progression and oxaliplatin resistance both in vitro and in vivo .

CONCLUSION

The study concludes that PRNT is upregulated in oxaliplatin-resistant CRC cells and modulates the expression of HIPK2 by sponging ZNF184. This regulatory mechanism enhances CRC progression and resistance to oxaliplatin, positioning PRNT as a promising therapeutic target for CRC patients undergoing oxaliplatin-based chemotherapy.
Success rate of current human-derived gastric cancer organoids establishment and influencing factors: A systematic review and meta-analysis
Authors: Jiang Kai-Lin , Wang Xiang-Xiang , Liu Xue-Jiao , Guo Li-Kun , Chen Yong-Qi , Jia Qing-Ling , Yang Ke-Ming , Ling Jiang-Hong
Published: April 2024

BACKGROUND

Human-derived gastric cancer organoids (GCOs) are widely used in gastric cancer research; however, the culture success rate is generally low.

AIM

To explore the potential influencing factors, and the literature on successful culture rates of GCOs was reviewed using meta-analysis.

METHODS

PubMed, Web of Science, and EMBASE were searched for studies. Two trained researchers selected the studies and extracted data. STATA 17.0 software was used for meta-analysis of the incidence of each outcome event. The adjusted Methodological Index for Non-Randomized Studies scale was used to assess the quality of the included studies. Funnel plots and Egger’s test were used to detect publication bias. Subgroup analyses were conducted for sex, tissue source, histological classification, and the pathological tumor-node-metastasis (pTNM) cancer staging system.

RESULTS

Eight studies with a pooled success rate of 66.6% were included. GCOs derived from women and men had success rates of 67% and 46.7%, respectively. GCOs from surgery or biopsy/endoscopic submucosal dissection showed success rates of 70.9% and 53.7%, respectively. GCOs of poorly-differentiated, moderately-differentiated and signet-ring cell cancer showed success rates of 64.6%, 31%, and 32.7%, respectively. GCOs with pTNM stages I-II and III-IV showed success rates of 38.3% and 65.2%, respectively. Y-27632 and non-Y-27632 use showed success rates of 58.2% and 70%, respectively. GCOs generated with collagenase were more successful than those constructed with Liberase TH and TrypLE (72.1% vs 71%, respectively). EDTA digestion showed a 50% lower success rate than other methods (P = 0.04).

CONCLUSION

GCO establishment rate is low and varies by sex, tissue source, histological type, and pTNM stage. Omitting Y-27632, and using Liberase TH, TrypLE, or collagenase yields greater success than EDTA.
Associations between COVID-19 and Glucose-6-Phosphate Dehydrogenase Activity in Brazil
Authors: de Almeida Rodrigues Maria Gabriela , Monteiro Wuelton Marcelo , de Melo Gisely Cardoso , Dias Ádila Liliane Barros , Sartim Marco Aurélio , Xavier Mariana Simão , Netto Rebeca Linhares Abreu , Almeida Fernando Fonseca , Baía-da-Silva Djane Clarys , Brito-Sousa José Diego , de Lacerda Marcus Vinicius Guimarães , de Souza Sampaio Vanderson
Published: April 2024

Glucose-6 phosphate dehydrogenase deficiency (G6PDd) was suggested as a risk factor for severe disease in patients with COVID-19. We evaluated clinical outcomes and glucose-6 phosphate dehydrogenase (G6PD) activity during and after illness in patients with COVID-19. This prospective cohort study included adult participants (≥ 18 years old) who had clinical and/or radiological COVID-19 findings or positive reverse transcription–polymerase chain reaction results. Epidemiological and clinical data were extracted from electronic medical records. Glucose-6 phosphate dehydrogenase activity was measured using SD Biosensor STANDARD G6PD® equipment on admission and 1 year after discharge. Samples were genotyped for the three most common single nucleotide polymorphisms for G6PDd in the Brazilian Amazon. Seven hundred fifty-three patients were included, of whom 123 (16.3%) were G6PD deficient. There was no difference between groups regarding the risks of hospitalization (P = 0.740) or invasive mechanical ventilation (P = 0.31), but the risk of death was greater in patients with normal G6PD levels (P = 0.022). Only 29 of 116 participants (25%) carried the African G6PDd genotype. Of 30 participants tested as G6PD deficient during disease, only 11 (36.7%) results agreed 1 year after discharge. In conclusion, this study does not demonstrate an association of G6PDd with severity of COVID-19. Limitations of the test for detecting enzyme levels during COVID-19 illness were demonstrated by genotyping and retesting after the disease period. Care must be taken when screening for G6PDd in patients with acute COVID-19.
A Mixed-Methods Evaluation of Mainstreaming Mass Drug Administration for Schistosomiasis and Soil-Transmitted Helminthiasis in Four Districts of Nigeria
Authors: Griswold Emily , Eigege Abel , Emukah Emmanuel C. , Gallagher Jayden Pace , Coalson Jenna , Rakers Lindsay , Mancha Bulus , Ndudi Okocha , Ugbadamu Paul , Dikedi Philomena , Poko Happiness , Danboyi Jacob , Dagwa Philemon , Anighoro Vincent , Gwong Christiana Davou , Otabor Esther , Amayat Goodluck James , Unukopia Regina Ese , Miri Emmanuel S. , Noland Gregory S.
Published: April 2024

In Nigeria, mass drug administration (MDA) for schistosomiasis (SCH) and soil-transmitted helminthiasis (STH) has often been coordinated with other programs that receive greater external funding. As these programs reach stop MDA milestones, SCH and STH programs will likely need to transition implementation, or “mainstream,” to domestic support. A mixed-methods study was conducted in four districts before (2021) and after (2022) mainstreaming to evaluate its impact on MDA coverage. Household surveys were done in 30 villages per district pre- and post-mainstreaming. All selected communities were eligible for STH treatment; around a third were eligible for SCH treatment. Mass drug administration was primarily conducted in schools. A total of 5,441 school-aged children were included in pre-mainstreaming and 5,789 were included in post-mainstreaming. Mass drug administration coverage was heterogeneous, but overall, mebendazole coverage declined nonsignificantly from 81% pre-mainstreaming to 76% post-mainstreaming (P = 0.09); praziquantel coverage declined significantly from 73% to 55% (P = 0.008). Coverage was significantly lower among unenrolled children or those reporting poor school attendance in nearly every survey. For the qualitative component, 173 interviews and 74 focus groups were conducted with diverse stakeholders. Respondents were deeply pessimistic about the future of MDA after mainstreaming and strongly supported a gradual transition to full government ownership. Participants formulated recommendations for effective mainstreaming: clear budget allocation by governments, robust and targeted training, trust building, and comprehensive advocacy. Although participants lacked confidence that SCH and STH programs could be sustained after reductions in external support, initial results indicate that MDA coverage can remain high 1 year into mainstreaming.
Risk Factor Analysis of Cutaneous Leishmaniasis in Sri Lanka through a Nationwide Survey
Authors: Dewasurendra Rajika , Samaranayake Nilakshi , Silva Hermali , Manamperi Nuwani , Senerath Upul , Senanayake Sanath , de Silva Nissanka , Karunanayake Panduka , Zhou Guofa , Karunaweera Nadira
Published: April 2024

Leishmaniasis in Sri Lanka was first reported in the early 1990s. Cutaneous leishmaniasis (CL) cases have markedly increased in recent years, demanding due attention from health authorities. The spatial distribution of CL is not homogeneous. This case-control study investigated factors that may contribute to this heterogeneous distribution through a nationwide study. Information on sociodemographic, economic, and environmental characteristics was collected from study participants (cases, n = 303; controls, n = 2,762). All individuals were followed up for 3 years, and signs of CL or associated complications were recorded. Differences in possible risk factors between cases and controls were analyzed. Individuals <18 years old, electricity supply, spending >2 hours outdoors, visiting jungles/water bodies, and living near CL patients were identified as risk factors. Household members of 1.3% of cases, 2.3% of controls residing within a perimeter of 500 m from a patient, and 0.8% of controls living beyond 2 km from a case developed CL. Thus, CL in Sri Lanka appears intertwined with living environment and host behavior. Common environmental factors may be responsible for the higher risk of CL in individuals living in close proximity to CL patients. This may at least partly explain the clustering of CL cases in selected areas of the country.
Diagnostic Communication with Zero Emission Vehicles (ZEV) Using ISO 14229-5 (UDS on IP) and SAE J1979-3 (ZEV on UDS)
Authors: Subke Peter , Heineman Lindsey , Mayer Julian
Published: April 2024

SAE J1979 and its “OBD Modes” served for the protection of our environment against harmful pollutants for decades, but due to regulatory adoption of Unified Diagnostic Services (UDS), SAE J1979 has now become a multiple part document series: SAE J1979 will be replaced by SAE J1979-2 for vehicles with combustion engines (ICEs) and by SAE J1979-3 for Zero Emission Vehicle (ZEV) propulsion systems. For ZEVs, emission-related failures will be replaced by ZEV propulsion-related failures.

Both SAE J1979-2 and -3 are variants of ISO 14229 (UDS) but limited to emission-related and ZEV propulsion-related failures, respectively, and associated diagnostic data. These new diagnostic communication protocols are required by California Air Resources Board (CARB) but do not support vehicle-manufacturer-specific diagnostic applications like calibration or flash programming. For performance reasons of the flash process, the deployment of UDS on Internet Protocol (UDSonIP) as it is standardized in ISO 14229-5 became state-of-the art.

This paper describes the basics of UDSonIP, Diagnostic communication over Internet Protocol (DoIP) and ZEVonUDS. It also covers how DoIP is used for diagnostic communication with the ZEV propulsion system to read the VIN. Finally, it provides a comparison between DoIP and Diagnostic communication over Controller Area Network (DoCAN), based on the analysis of a hex dump.
Trajectory Tracking Control of Unmanned Vehicle Formation Based on Full-Order Sliding Mode
Authors: Zhou Minghao , Chen Jiaxin , Cai Wei , Fei Xueran
Published: April 2024

A novel control method based on full-order sliding mode is proposed in this paper to solve the trajectory tracking control problem of unmanned vehicle formation. The complexity of the unmanned vehicle system is considered and a dynamic error model of the system is established . A full-order sliding mode control method is adopted to realize the cooperative control of unmanned vehicle systems. The unmanned vehicle system can force each vehicle accurately track the specified trajectory. The simulation results show that the designed full-order sliding mode control method has excellent performance compared with the traditional linear sliding mode control in terms of accuracy and robustness. In the case of large changes in different types of road surface and vehicle dynamics, the movement of unmanned vehicles is effectively controlled, and the trajectory tracking control of unmanned vehicle formation system is realized.
A Target-Speech-Feature-Aware Module for U-Net Based Speech Enhancement
Authors: Pei Kaikun , Zhang Lijun , Meng Dejian , He Yinzhi
Published: April 2024

Speech enhancement can extract clean speech from noise interference, enhancing its perceptual quality and intelligibility. This technology has significant applications in in-car intelligent voice interaction. However, the complex noise environment inside the vehicle, especially the human voice interference is very prominent, which brings great challenges to the vehicle speech interaction system. In this paper, we propose a speech enhancement method based on target speech features, which can better extract clean speech and improve the perceptual quality and intelligibility of enhanced speech in the environment of human noise interference. To this end, we propose a design method for the middle layer of the U-Net architecture based on Long Short-Term Memory (LSTM), which can automatically extract the target speech features that are highly distinguishable from the noise signal and human voice interference features in noisy speech, and realize the targeted extraction of clean speech. Then, in order to achieve deep fusion between the target speech features and the model, we design a multi-scale deep fusion skip connection method, so that when the effective information flows from the encoder to the decoder, the features with large correlation with the target speech are effectively screened through the weight coefficient of attention. Finally, in order to verify the effectiveness of the proposed module, experiments were carried out on the Voicebank+Demand speech dataset. The results show that the proposed method has strong robustness in the environment with human voice interference. It outperforms other algorithms on metrics such as PESQ, STOI, CSIG, CBAK, COVL, offering cleaner speech with higher perceptual quality and intelligibility. This makes it particularly promising for applications in scenarios with significant human voice interference, such as in-car environments.
Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications
Authors: Brown Nicolas Eric , Patil Pritesh , Sharma Sachin , Kadav Parth , Fanas Rojas Johan , Hong Guan Yue , DaHan Liao , Ekti Ali , Wang Ross , Meyer Rick , Asher Zachary
Published: April 2024

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.
Construction of Terrain Multidimensional Traversibility Feature Map for Off-Road Scenarios Based on Binocular Vision
Authors: Liu Yanchen , Zhao Jian , Zhang Jian , Leng Zhiyuan , Chen Jia
Published: April 2024

Terrain Traversability Feature (TTF) map, which could be constructed by the images and point cloud data base on binocular vision, often using multi-frame fusion technology to expand the coverage area. However, the common challenges of off-road scenarios such as missing GPS data or single terrain features seriously hindered the alignment of adjacent frame data. Additionally, traditional TTF map depict the vehicle's surroundings only based on a few features such as terrain elevation or category. And it is insufficient for complex off-road scenarios navigation tasks.

This paper presents a method for constructing a Terrain Multidimensional Traversability Feature (TMTF) map for off-road scenarios based on binocular vision. First, we utilize the point cloud data from a binocular camera to construct a grid map model. Therefore, the geometric features of the terrain could be calculated with the grid as the basic unit, and a single-frame TMTF map of off-road scenarios is established. Subsequently, we propose an adhesion coefficient estimation method based on image semantics considering uncertainty, which successfully helps TMTF map to further describe the terrain category and mechanical characteristics. Then, an inter-frame pose transformation estimation method integrating wheel speed and direct method visual odometry is designed. It registers and fuses the historical and current TMTF maps to expands the vehicle's perception range, and effectively solves missing GPS data and single terrain features of off-road scenarios.

Finally, the test and verification are carried out based on the playback of the collected real vehicle data. The test results clearly demonstrate the constructed TTFM effectively represents multi-dimensional features like terrain type, geometry, and mechanics in off-road environments. At the same time, the traversability feature description of non-visible areas is successfully supplemented through fusion of multi-frame TMTF map.
Optimizing Urban Traffic Efficiency via Virtual Eco-Driving Featured by a Single Automated Vehicle
Authors: Ozkan Mehmet F. , Gupta Shobhit , D'Alessandro Stefano , Spano Matteo , Kibalama Dennis , Paugh Jacob , Canova Marcello , Stockar Stephanie , Reese Ronald A. , Wasacz Bryon
Published: April 2024

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy. Then, a microscopic traffic model that represents the driving behaviors of the human-driven vehicle queue is introduced to investigate the overall energetic impact of the eco-driving strategy on human-driven vehicles in urban routes. Two different scenarios are considered, one involving human-driven vehicles following a lead human-driven vehicle, and the other with the human-driven vehicles led by the CAV. The results reveal that CAV not only achieves high energy savings for the CAV itself but also improves the fuel economy of the following human-driven vehicles without featuring any cooperative driving. The findings highlight that even with a low penetration rate, CAVs could reduce the overall energy usage of a cohort of uncoordinated vehicles in urban traffic scenarios by as much as 7% - 27% when used as virtual eco-driving controllers.
Effects of Spark Plug Operating Conditions on Electrode Erosion and Surface Deformation
Authors: Tambasco Corey , Hall Matthew , Matthews Ron
Published: April 2024

An experimental study of the spark ignition process for SI engines was conducted to study spark plug erosion and the effect of breakdown voltage/energy on electrode surface deformation. The experiments were conducted outside of an engine, in both a pressurized constant volume optical chamber and in a high-pressure vessel heated within a furnace with gas temperatures as high as 730°C. J-gap spark plugs designed for natural gas engines were studied at elevated temperature and under a range of pressures to investigate electrode wear characteristics. Both iridium-alloy and platinum-alloy cathode (center electrode) and anode (ground strap) spark plugs were investigated. In addition, single spark events were performed on polished platinum cathode surfaces to allow the visualization of craters from individual spark events in order to quantify how their size and shape were affected by energy deposition and breakdown characteristics. The spark plug electrodes were investigated using optical profilometry, scanning electron microscopy (SEM), and energy dispersive X-ray (EDX) analysis. The furnace erosion tests were run with up to 30 million spark events for a given spark plug. The breakdown voltage was found to generally increase, as expected, with increasing electrode wear as the number of spark events increased. The rate of increase of the breakdown voltage was greatest during the early portion of a trial, presumably as the relatively sharp edges of the center electrode experienced wear. Consistent with prior studies, platinum-based spark plugs were found to erode significantly more than iridium-based plugs under identical scenarios.
A Study on Overcoming Unavailable Backward Driving and a New Fail-Safe Strategy for R-Gearless (P)HEV System
Authors: Rho Jeongwon , Park Chilseong , Kim Taejin , Kim Yonghyun , Hong Eui Sun , Park Daero
Published: April 2024

Recently, as part of the effort to enhance fuel efficiency and reduce costs for eco-friendly vehicles, the R-gearless system has been implemented in the TMED (P)HEV system. Due to the removal of the reverse gear, a distinct backward driving method needs to be developed, allowing the Electronic Motor (e-Motor) system to facilitate backward movement in the TMED (P)HEV system. However, the capability of backward driving with the e-Motor is limited because of partial failure in the high-voltage system of an R-gearless system. Thus, we demonstrate that it is possible to improve backward driving problems by applying a new fail-safe strategy. In the event of a high-voltage battery system failure, backward driving can be achieved using the e-Motor with constant voltage control by the Hybrid Starter Generator (HSG), as proposed in this study. The introduction of feed-forward compensation for variable constant voltage control allows for the securement of more active output power within the confines of limited HSG output power. In the case of HSG failure, the risk of overcharging the high-voltage main battery due to the back electromotive force of the HSG exits necessitates the disconnection of the main relay. However, the proposed high-voltage battery protection strategy in this study resolves this issue, enabling the maintenance of the main relay closure for backward driving through the use of the e-Motor. In the event of a control area network failure, a redundancy system permits the passage of e-Motor power, ensuring the availability of backward driving. Furthermore, if backward driving becomes unattainable due to e-Motor failure or similar issues, system fail-safety is upheld by providing the driver with a warning notification and automatically engaging the electric parking brake system.
The Effects of Cathode Channel Side Blockage on Enhanced Performance of a Proton Exchange Membrane Fuel Cell
Authors: Zheng Yang
Published: April 2024

Flow channels in proton exchange membrane fuel cells (PEMFC) play an irreplaceable role, and flow channel design in bipolar plates is one of the most active research areas at present. The flow channel on the cathode side needs to discharge liquid water out of the fuel cell in time and allow oxygen to flow to the cathode catalytic layer as much as possible to avoid the phenomenon of cathode water flooding and mass transfer loss. In order to improve the performance of PEMFC, a method of setting both side blockages in the cathode flow channel is proposed. In this paper, lateral blockage models with three shapes are proposed to study the influence of blockage on mass transfer and performance. First, a 3D PEMFC model with a middle channel was built to calculate the fuel cell power at different discharge rates. Secondly, a preliminary three-dimensional model of the blockage in the cathode flow channel of the fuel cell was established, a simulation analysis was carried out to study the influence of blockage shape on mass transfer, and an optimization analysis was carried out. The study found that the blockage's cross-sectional shape greatly influenced mass transfer enhancement in PEMFC. Compared with the straight-through channel, the arrangement of lateral blockages can increase the oxygen concentration in the diffusion layer, which can help discharge liquid water and effectively improve the performance of PEMFC. It was determined that the best fuel cell performance at high current density was achieved when the blockage shape was P2. At a current density of 1.5 A cm2, a blockage with a flow-conducting structure P2 helped to remove the liquid water at this interface, improving the cell performance by 17% PEMFC can obtain excellent performance.
Tackling Limited Labeled Field Data Challenges for State of Health Estimation of Lithium-Ion Batteries by Advanced Semi-Supervised Regression
Authors: Li Jinwen , Chen Wenqiang , Khalatbarisoltani Arash , Liu Hongao , Lin Xianke , Hu Xiaosong
Published: April 2024

Accurate estimation of battery state of health (SOH) has become indispensable in ensuring the predictive maintenance and safety of electric vehicles (EVs). While supervised machine learning excels in laboratory settings with adequate SOH labels, field-based SOH data collection for supervised learning is hindered by EVs' complex conditions and prohibitive data collection costs. To overcome this challenge, a battery SOH estimation method based on semi-supervised regression is proposed and validated using field data in this paper. Initially, the Ampere integral formula is employed to calculate SOH labels from charging data, and the error of labeled SOH is reduced by the open-circuit voltage correction strategy. The calculation error of the SOH label is confirmed to be less than 1.2%, as validated by the full-charge test of the battery packs. Subsequently, statistical features are extracted from charging data, and health indicator sets are selected by two correlation analysis methods (Pearson correlation and grayscale correlation). Moreover, two regressors are trained by learning the mapping between labeled SOH and various health indicator sets. To enhance the training dataset, semi-supervised with co-training is utilized to estimate pseudo-labels for unlabeled charging data. The final SOH estimation is achieved through the fusion of these two regressors. Finally, the proposed method is validated using field data from 20 electric forklifts collected over approximately one year. Remarkably, even with only 10 labeled data points, the proposed method achieves a mean absolute error in SOH estimation of a mere 3.96%. This represents a significant reduction of 20% compared to the traditional supervised learning method. Compared with the two benchmarks without co-training, the estimation error drops by 7.69% and 8.76%, respectively.
Maximum Pulling Force Calculation of Permanent Magnet Tractor Motors in Electric Vehicle Applications
Authors: Gong Cheng , Chang Le , He Song , Zhang Peng , Muir Michael
Published: April 2024

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core. The impact of asymmetric air gap as well as temperature is analyzed for comprehensiveness. It shows that the asymmetric air gap can cause about 2.7% higher force. Finally, the dummy non-slotted cylinder stator is swapped with a slotted stator for better model fidelity. FEA shows that the slotted stator can have 21% lower force than a dummy cylinder stator. Although the method and conclusions proposed in this paper are based on a case study of one motor, they are still valid and applicable to other traction motors in a more generalized sense and can serve as a good reference for the EV motor industry for a safer and more efficient manufacturing assembly.
Mapping an Optimum DC-Link Voltage across the Entire SiC-Based EV Drive Regions Using a Synchronous Boost DC-DC Converter
Authors: Amirpour Sepideh , Thiringer Torbjörn , Xu Yu
Published: April 2024

When designing an electric vehicle (EV) traction system, overcoming the issues arising from the variations in the battery voltage due to the state of charge (SoC) is critical, which otherwise can lead to a deterioration of the powertrain energy efficiency and overall drive performance. However, systems are typically documented under fixed voltage and temperature conditions, potentially lacking comprehensive specifications that account for these variations across the entire range of the vehicle operating regions. To tackle this challenge, this paper seeks to adjust an optimal DC-link voltage across the complete range of drive operating conditions by integrating a DC-DC converter into the powertrain, thereby enhancing powertrain efficiency. This involves conducting a comprehensive analysis of power losses in the power electronics of a connected converter-inverter system considering the temperature variations, along with machine losses, accounting for variable DC-link voltages. The results reveal that the inclusion of a DC-DC converter into a powertrain is advantageous, particularly for low battery terminal voltages. Consequently, the powertrain system, incorporating a DC-DC boost converter, exhibits lower total loss values, with a difference of up to 5 kW loss difference for high-speed, low-torque regions compared to the case when not incorporating the DC-DC converter.
Inverse Analysis of Road Contact Force and Contact Location Using Machine Learning with Measured Strain Data
Authors: Yamaki Yuya , Tsuji Shohei , Zama Kazuhiro , Ogata Takanori , Okuhira Yoichiro
Published: April 2024

To adapt to Battery Electric Vehicle (BEV) integration, the significance of protective designs for battery packs against ground impact caused by road debris is very high, and there is also a keen interest in the feasibility assessment technique using Computer-Aided Engineering (CAE) tools for prototype-free evaluations. However, the challenge lies in obtaining real-world empirical data to verify the accuracy of the predictive CAE model. Collecting real-world data using actual battery pack can be time-consuming, costly, and accurately ascertaining the precise direction, magnitude, and location of the force applied from the road to the battery pack poses a challenging task. Therefore, in this study, we developed a methodology using machine learning, specifically Gaussian process regression (GPR), to perform inverse analysis of the direction, magnitude, and location of vehicle-road contact forces during rough road conditions. This was achieved by measuring the strain distribution of the plate-like device attached to the vehicle's underbody, as explanatory variables for the regression. To create a regression model, strain distribution patterns of the measurement device were gathered as a training dataset by altering the direction, magnitude, and application location of the forces in a laboratory environment. Finally, we conducted a test on a bumpy test road at different speeds (20km/h and 30km/h) to assess the vehicle-road interaction. We qualitatively confirmed the reliability of the analysis results regarding the time series data of the direction, magnitude, and location of vehicle-road contact forces obtained through regression by comparing them with contact marks on the device, vehicle behavior captured by a high-speed camera, and deformation of the device measured using laser displacement sensors, verifying their consistency. The findings were employed to identify parameters to be set in predictive CAE further expediting Model-Based Development (MBD).
An Adaptive Clamping Force Control Strategy for Electro-Mechanical Brake System Considering Nonlinear Friction Resistance
Authors: Xu Zelin , Wu Jian , Bi Gongyuan , Hou Jie , Zheng Wenbo , Li Lun , Gao Shang , Chen Zhicheng
Published: April 2024

The Electronic Mechanical Braking (EMB) system, which offers advantages such as no liquid medium and complete decoupling, can meet the high-quality active braking and high-intensity regenerative braking demands proposed by intelligent vehicles and is considered one of the ideal platforms for future chassis. However, traditional control strategies with fixed clamping force tracking parameters struggle to maintain high-quality braking performance of EMB under variable braking requests, and the nonlinear friction between mechanical components also affects the accuracy of clamping force control. Therefore, this paper presents an adaptive clamping force control strategy for the EMB system, taking into account the resistance of nonlinear friction. First, an EMB model is established as the simulation and control object, which includes the motor model, transmission model, torque balance model, stiffness model, and friction model. Subsequently, a cascaded clamping force controller, consisting of clamping force loop, velocity loop, and current loop, is designed for EMB using Proportional-Integral (PI) control theory. On this basis, fuzzy theory is applied to adaptively adjust the PI control coefficients of the clamping force loop, and an Extended State Observer (ESO) is introduced in the current loop to dynamically estimate and compensate for the friction resistance of the EMB system. Finally, a simulation platform is established using MATLAB/Simulink for testing and validation. Simulation results demonstrate that ESO accurately estimates the friction torque in real-time, and the proposed adaptive clamping force control strategy effectively controls the EMB to overcome non-linear friction resistance, with a clamping force tracking error of less than 2% for an 8Hz sine wave input. Moreover, the controller exhibits good adaptability, maintaining high-quality control performance even after altering the simulated control object's friction characteristics.
A Path Tracking Method for an Unmanned Bicycle Based on the Body-Fixed Coordinate Frame
Authors: Cheng Kaizhuo , Duan Yupeng , Wu Jinglai , Zhang Yunqing
Published: April 2024

The present study introduces a novel approach for achieving path tracking of an unmanned bicycle in its local body-fixed coordinate frame. A bicycle is generally recognized as a multibody system consisting of four distinct rigid bodies, namely the front wheel, the front fork, the body frame, and the rear wheel. In contrast to most previous studies, the relationship between a tire and the road is now considered in terms of tire forces rather than nonholonomic constraints. The body frame has six degrees of freedom, while the rear wheel and front fork each have one degree of freedom relative to the body frame. The front wheel exhibits a single degree of freedom relative to the front fork. A bicycle has a total of nine degrees of freedom. The expression of the kinetic energy of a bike is formulated using quasi-coordinates in the local body-fixed coordinate frame, which provides a more simplified representation compared to the utilization of absolute coordinates in the global coordinate frame. The acquisition of the dynamic model involves the substitution of the expression of kinetic energy into the Lagrange equation. The application of the Lagrange equation of the second kind is computationally efficient but the derivation is difficult. The derivation using the Lagrange equation of the first kind is relatively simple, but its computational efficiency is poor. The present study combines two methods by dividing the bicycle from the steering pivot into two rigid body groups, applying the Lagrange equation of the second kind in each group, and then applying the Lagrange equation of the first kind to both groups. This method is simple to derive and has good computational efficiency. The path is strategically organized in the body coordinate frame to circumvent possible singularity issues in the global coordinate frame. A dual-loop PID controller is implemented to achieve path tracking where the inner loop controller is responsible for maintaining the stability of the bicycle, while the outer loop controller ensures that the bicycle follows the desired path.
Pantograph Optimization Design Based on the Model of Mining Truck-Road-Pantograph
Authors: Qian Shuo , Shen Yanhua , Wang Kaidi , Liu Zuyang
Published: April 2024

This study focuses on the operation of trolley-assisted mining truck, which leverage overhead lines for uphill propulsion, substantially reducing fuel consumption and carbon emissions. The pantograph mounted at the truck body's front exhibits complex vibrational behavior due to the subgrade stiffness and the nonlinearities of the hydro-pneumatic suspension. Vertical dynamic model of the mining truck is constructed which considering the road conditions and suspension characteristics to illustrate the pantograph's contact force. The vibration characteristic of pantograph base is analyzed which using the spatial transformation relationship between the truck's center mass of gravity and the base of pantograph. The stiffness of pantograph is designed based on a pantograph-catenary system model considering different road conditions. The real mining truck is modeled in the Trucksim software to obtain the vibration of pantograph base. And the effectiveness of the pantograph stiffness can be verified through co-simulation of Trucksim-Simulink. Finally, an MPC active controller is designed to reduce the fluctuation of contact force between the pantograph and the catenary by providing active force. The simulation results have shown that the optimized pantograph parameters can meet pantograph-catenary contact requirements and the controller can effectively reduce the pantograph head vibration and contact force fluctuations.
Modeling & Validation of a Digital Twin Tracked Vehicle
Authors: Daly Nicholas , Manvi Pranav , Chhatbar Tanmay , Schmid Matthias , Castanier Matthew P. , Wagner John
Published: April 2024

Digital twin technology has become impactful in Industry 4.0 as it enables engineers to design, simulate, and analyze complex systems and products. As a result of the synergy between physical and virtual realms, innovation in the “real twin” or actual product is more effectively fostered. The availability of verified computer models that describe the target system is important for realistic simulations that provide operating behaviors that can be leveraged for future design studies or predictive maintenance algorithms. In this paper, a digital twin is created for an offroad tracked vehicle that can operate in either autonomous or remote-control modes. Mathematical models are presented and implemented to describe the twin track and vehicle chassis governing dynamics. These components are interfaced through the nonlinear suspension elements and distributed bogies. The assembled digital twin’s performance was investigated using test data collected from the Clemson University Deep Orange 13/14 tracked vehicles. The prototype vehicle completed a series of operating scenarios with both on-board data collection and video monitoring to document the performance. Similar scenarios were emulated in the digital twin virtual environment. Representative numerical and field results will be collectively presented to demonstrate the performance of the digital twin in estimating the real twin behavior. This virtual tool, with coupling option to/from the physical system, establishes a foundation for predictive maintenance and next generation vehicle design studies.
A Method for Identifying the Noise Characteristics of an Electric Motor System Based on Tests Conducted under Distinct Operating Conditions
Authors: Zuo Shuguang , Mao Qingshao
Published: April 2024

The noise tests of electric motor systems serve as the foundation for studying their acoustic issues. However, there is currently a lack of corresponding method for identifying key noise characteristics, such as the noise frequency range that needs to be considered, the significant noise order, and the resonance band worth paying attention to, based on experimental test data under actual operating conditions. This article proposes a method for identifying the noise characteristics of an electric motor system based on tests conducted under distinct operating conditions, which consists of three parts: identifying the primary frequency range, the significant order, and the important resonance band.

Firstly, in order to extract noise with the primary energy, the concept of noise contribution is introduced. The primary frequency range and the significant order under a specific operating condition can be obtained after extraction. Then, for the purpose of identifying the important resonance band, a method called assumed order scanning is proposed derived from the characteristic that noise orders reach the local maximum when they are passing through resonance bands. Finally, noise characteristics identification is performed on the experimental test of an electric sit-stand desk, which validates the effectiveness of the proposed method.

In contrast with the usual way to get noise characteristic from experimental data, the method presented in this article effectively utilizes data to acquire valuable information, facilitating quantitative analysis and batch processing. Furthermore, this approach can offer guidance for noise control requirements in engineering practice. This method is applicable to noise tests related to electric motors and provides a reference for data processing in such tests.
Experimental Study of Ammonia Combustion in a Heavy-Duty Diesel Engine Converted to Spark Ignition Operation
Authors: Alvarez Luis F. , Dumitrescu Cosmin E.
Published: April 2024

Ammonia is one of the carbon-free alternatives considered for power generation and transportation sectors. But ammonia’s lower flame speed, higher ignition energy, and higher nitrogen oxides emissions are challenges in practical applications such as internal combustion engines. As a result, modifications in engine design and control and the use of a secondary fuel to initiate combustion such as natural gas are considered for ammonia-fueled engines. The higher-octane number of methane (the main component in natural gas) and ammonia allows for higher compression ratios, which in turn would increase the engine's thermal efficiency. One simple approach to initiate and control combustion for a high-octane fuel at higher compression ratios is to use a spark plug. This study experimentally investigated the operation of a heavy-duty compression ignition engine converted to spark ignition and ammonia-methane blends. Engine operation at a 40% natural gas energy substitution rate with ammonia was compared with methane-only engine operation at low speed (900 rpm), lean conditions (equivalence ratio of 0.85) and medium load (7 bar indicated mean effective pressure). The spark timing was varied from -25 CA to -10 CA ATDC to evaluate if a change in spark timing is needed when ammonia is added. Results show that, as expected, advancing the spark timing led to increased and advanced peak pressure and heat release rate, and increased nitrogen oxides emissions. Then, replacing the natural gas with ammonia decreased and retarded in-cylinder pressure due to the associated decrease in the flame propagation rate. However, replacing the natural gas with ammonia at a 40% energy replacement level did not affect the indicated mean effective pressure, thermal efficiency, or the optimum spark timing of -20 CA ATDC, but NOx emissions increased substantially.