Experimental Verification Research Articles

IMPLEMENTATION OF IO-LINK TECHNOLOGY INTO THE HANDLING AND SORTING SUB-STATION OF THE FESTO FMS 500 AUTOMATED LINE

The article deals with implementing IO-LINK components in the sorting station of the FESTO FMS 500 automated line and their experimental verification based on the principles of IO-LINK technology. The implementation of such technology also includes the upgrade of the PLC control to PLC S7-1500 (SIEMENS), the addition of an IO-LINK device (BALLUFF BNI005H), and a signaling light device from the same company (SMARTLIGHT BNI007F), which ensures the indication of workplace state. Communication between the PLC device and the IO-LINK devices is carried out via the PROFINET communication network. Installing the signaling light device at the sorting station of the automated line provides light signaling messages for the operator (concerning the standard STN EN 61310-1). For example, the indication of the filling of the reserve warehouse using a light signaling message means the operator needs to empty the individual warehouses to repeat the sorting operation. In addition, part of the article is the implementation and evaluation of experimental measurements, the aim of which is to determine both the individual sorting times of various components, as well as determining their maximum number during the sorting process in connection with increasing the level of automation of the sorting station as such.

Investigation of the active ingredients and mechanism of Shuangling extract in dextran sulfate sodium salt induced ulcerative colitis mice based on network pharmacology and experimental verification.

To explore the pharmacodynamic effects and potential mechanisms of Shuangling extract against ulcerative colitis (UC). The bioinformatics method was used to predict the active ingredients and action targets of Shuangling extract against UC in mice. And the biological experiments such as serum biochemical indexes and histopathological staining were used to verify the pharmacological effect and mechanism of Shuangling extract against UC in mice. The Shuangling extract reduced the levels of seruminterleukin-1β (IL-1β), tumor necrosis factor-α (TNF-N), interleukin-6 (IL-6) and other inflammatory factors in UC mice and inhibited the inflammatory response. AKT Serine/threonine Kinase 1 and IL-6 may be the main targets of the anti-UC action of Shuangling extract, and the TNF signaling pathway, Forkhead box O signaling pathway and T-cell receptor signaling pathway may be the main signaling pathways. The Shuangling extract could inhibit the inflammatory response induced by UC and regulate intestinal immune function through multiple targets and multiple channels, which provided a new option and theoretical basis for anti-UC.

A Novel Consequent-Pole Magnetic Lead Screw and its 3-D Analytical Model With Experimental Verification for Wave Energy Conversion

A Novel Consequent-Pole Magnetic Lead Screw and its 3-D Analytical Model With Experimental Verification for Wave Energy Conversion

Sensorless speed controller of an induction motor with MRAS-based model predictive control

Speed sensors play critical role in induction motor (IM) control systems. However, the use of these sensors cause several drawbacks such as increasing the overall cost, decreased reliability on control and increased noise problems in data acquisition. The sensorless control methods also have been proposed in control systems of IM to increase the overall performance. On the other hand, model predictive controllers (MPCs) which is one of the most recently used controller methods require the speed measurement to perform speed and torque control of an IM. In addition to control method, the topology of voltage source inverter (VSI) affects the overall efficiency of the IM drive because of its losses and total harmonic distortion (THD) ratios delivered by the topology. The main proposal of this study is to implement an IM drive built with a three-level active neutral point clamped (3L-ANPC) voltage source inverter (VSI) and to propose an MPC that eliminates sensor requirement in speed control of IM. The proposed IM drive takes benefits of multilevel inverter topology, which reduces the torque ripple, enables low switching frequency and provides decreased harmonic distortion. The switching pulses of ANPC VSI are generated by the proposed sensorless MPC method for controlling the torque of IM. The modelling and experimental verification of the ANPC based IM drive have been carried out and the sensorless MPC controller has been validated in this study. There two types of model reference adaptive system (MRAS) have been proposed to ensure precise estimation of IM speed that should be supplied to MPC controller. These MRAS methods are titled as the rotor flux based model reference adaptive system (MRASF), and the stator current based model reference adaptive system (MRASCC) according to estimation references. The proposed MPC-based IM drive has been analyzed under variable speed and torque circumstances to detect the efficiency and reliability of MRASF and MRASCC algorithms. The efficiency indicators such as flux and torque responses, and speed control of the suggested MPC IM drive are validated with experimental analysis. The results of revealed that the IM effectively tracks the reference speed and produces the required torque depending to the precise control of proposed MPC algorithm.

Study on the Mechanism of Action of the Traditional Chinese Medical Prescription Gushukang in Treating Osteoporosis Based on Network Pharmacology and Experimental Verification.

Gushukang (GSK), a traditional Chinese medical prescription, has made a great and extensive contribution to the treatment of different forms of osteoporosis, but polypharmacology studies of its mechanism of action are lacking. This study investigates the pharmacological mechanism of osteoporosis using network pharmacology and molecular docking. Experimental verification was carried out to confirm the efficacy of GSK on RANKLinduced osteoclast differentiation in RAW264.7 cells to verify the network pharmacology studies. The effective chemical components and corresponding targets of osteoporosis with oral bioavailability of more than 30% and drug-like properties greater than 0.18 were searched in the TCMSP and TCM-ID databases. DrugBank, GeneCards, OMIM, TTD, and other databases were examined for targets related to osteoporosis. Using Cytoscape software, a network of possible TCM-active ingredient-osteoporosis targets was created. STRING software was used to create the networks of protein-protein interactions. The DAVID program was carried out to conduct GO and KEGG pathway enrichment analyses of the targets. Molecular docking and pattern of action analysis were carried out using software like AutoDock Vina and Discovery Studio Visualizer. The growth media for RAW264.7 cells contained varying doses of GSK serum and 50 ng/mL RANKL. The activity of TRAP was altered. Additionally, genes related to osteoclasts were examined using an RT-PCR assay. Network pharmacological analysis revealed that the primary efficacy targets of osteoporosis were PTGS2, PTGS1, HSP90AA1, NCOA2, ADRB2, ESR1, NCOA1, and AR. The pharmacological targets of osteoporosis may be mediated by substances including quercetin, kaempferol, luteolin, naringenin, icariin, anthocyanin, tanshinone IIA, and cryptotanshinone. GSK markedly inhibited RANKL-induced TRAP activity. qRT-PCR results revealed decreased expression of the PTGS2 and ADRB2 genes upon GSK treatment. The findings of network pharmacology, molecular docking, as well as experimental verification provide a new further study for elucidating the pharmacodynamic substance basis and polypharmacology mechanism of GSK in treating osteoporosis.

Effect of polymer crosslinking to the failure behavior of thermoplastic composite remelting interface: Molecular dynamics simulation and experimental verification

AbstractThe forming interface is the weak link of thermoplastic composite complex structures. To explore the effect of polymer crosslinking on the failure behavior of thermoplastic composite remelting interface using “Preforming + Remelting bonding” process, the all‐atom models of different types of interfaces were established, and a molecular dynamics (MD) simulation was conducted on the uniaxial tensile failure process of the remelting interface. The failure behavior of the remelting interface with different preforming processes was tested to verify the correctness of MD simulation, and the influencing mechanism of polymer crosslinking reactions in the preforming stage to the remelting interface properties was clarified. The results showed that the yield stress of the uncrosslinked interface reaches 283.2 MPa and 16.0% and 50.6% higher than that of the unilateral and bilateral crosslinked interfaces respectively. The polymer crosslinking reaction during the preforming stage will reduce the interlaminar bonding performance. The interlaminar shear strength (ILSS) of the uncrosslinked interface is 87.46 MPa and 7.21% and 27.36% higher than that of the unilateral and bilateral crosslinked interface respectively, and only 3.95% lower than that of the non‐remelting sample formed by standard process. This research provides a new approach for predicting and analyzing the effect of polymer crosslinking on remelting interface properties of thermoplastic composite using “Preforming + Remelting bonding” process.Highlights The failure behavior of different thermoplastic composite remelting interfaces was studied. MD simulation was conducted on the uniaxial tensile failure process of the remelting interface. The influencing mechanism of polymer crosslinking reactions in the preforming stage to the remelting interface properties was clarified. It is effective to explore the failure mechanism of thermoplastic remelting interface by MD simulation.

The Mechanism of Scopolamine’s Effect on Migration Function of Lung Cancer Cells: A Network Pharmacology and Bioinformatics Perspective

Background. This study utilized network pharmacology and bioinformatics analysis to identify the hub genes influenced by scopolamine in lung cancer. Methods. The effect of scopolamine on lung cancer was investigated by cell invasion assay and cell scratch assay. The analysis involved protein-protein interaction (PPI) networks topology analysis to identify these genes, and subsequent differential analysis and survival analysis were conducted using gene expression profile interaction analysis (GEPIA). Furthermore, the findings were supported by molecular docking experiments for verification. Results. Results from cell invasion and scratch assays suggest that scopolamine inhibits the migration of lung cancer cells. JAK2, JAK3, CCR5, and ACE were identified as the top four hub genes that have an impact on lung cancer. KEGG enrichment analysis revealed that the scopolamine response in lung cancer is significantly associated with ten pathways, including “neuroactive ligand-receptor interaction in cancer,” “PD-1 checkpoint pathway in cancer,” “chemokine signaling pathway,” “PD-L1 expression,” and others. Additionally, the expression levels of JAK2, JAK3, CCR5, and ACE were found to be correlated with survival in patients with lung cancer. Furthermore, molecular docking experiments demonstrated that scopolamine binds and forms stable complexes with the protein products of all four aforementioned genes. The main targets of scopolamine in the treatment of lung cancer are JAK2, JAK3, CCR5, and ACE. Conclusion. Scopolamine has a significant effect on various cellular functions in lung cancer cells, potentially reducing the likelihood of metastasis. Based on these findings, it is recommended to consider administering scopolamine as part of the preoperative phase for patients with lung cancer.

Numerical and Experimental Evaluation of Structured Material for Use in Multiscale Topology Optimization

Multiscale topology optimization is a powerful tool for engineers seeking a design with minimum weight and maximum stiffness, using a structured material in the form of a lattice structure. Furthermore, the current trend is to combine multiple lattice topologies in one component to achieve the best possible response to local loading conditions while minimizing weight. Therefore, herein, a numerical and experimental evaluation by compression tests in two directions is performed for six basic lattice topologies and two hypotheses are tested. The first hypothesis states that an additional weight saving of more than 30% can be achieved by a better choice of lattice topology. The second hypothesis is based on the manufacturing limitations of the laser powder bed fusion technology and the assumption that a favorable loading direction parallel to the building direction exists. The first hypothesis is only confirmed for loading in the direction parallel to the building direction and the second only for two lattice topologies. When both hypotheses are combined, the additional weight reduction of the multiscale topology optimization result is 44.5% according to the numerical results and 32.7% according to the experimental verification.

Interspectral Error Tracking and Compensation of DSDT in Satellite Internet of Things

With the rapid growth of satellite Internet of Things (SIoT) services, existing frequency band resources are insufficient to meet future business demands. To effectively address this issue, it is necessary to enhance the utilization of existing frequency resources. However, idle frequency resources are typically scattered across multiple bands and vary in bandwidth size. Direct Spectrum Division Transmission (DSDT), dividing a complete signal into sub-spectrum signals for transmission in idle frequency bands, can take the use of fragmented spectrum resources for satellite communication. Nevertheless, the performance of DSDT depends heavily on accurate synchronization toward multiple sub-spectrums. In this paper, an algorithm for error synchronization tracking and compensation is proposed by utilizing the focusing nature of constellation. All sub-spectrums are weighed by the minimum Euclidean distance of the constellation to compensate for amplitude–frequency–phase errors simultaneously. Simulations and experimental verification demonstrate synchronization performance and feasibility of proposed method in a multi-radio frequency channels environment.

Short-Term Traffic Flow Forecasting Method Based on Secondary Decomposition and Conventional Neural Network–Transformer

Because of the random volatility of traffic data, short-term traffic flow forecasting has always been a problem that needs to be further researched. We developed a short-term traffic flow forecasting approach by applying a secondary decomposition strategy and CNN–Transformer model. Firstly, traffic flow data are decomposed by using a Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) algorithm, and a series of intrinsic mode functions (IMFs) are obtained. Secondly, the IMF1 obtained from the CEEMDAN is further decomposed into some sub-series by using Variational Mode Decomposition (VMD) algorithm. Thirdly, the CNN–Transformer model is established for each IMF separately. The CNN model is employed to extract local spatial features, and then the Transformer model utilizes these features for global modeling and long-term relationship modeling. Finally, we obtain the final results by superimposing the forecasting results of each IMF component. The measured traffic flow dataset of urban expressways was used for experimental verification. The experimental results reveal the following: (1) The forecasting performance achieves remarkable improvement when considering secondary decomposition. Compared with the VMD-CNN–Transformer, the CEEMDAN-VMD-CNN–Transformer method declined by 25.84%, 23.15% and 22.38% in three-step-ahead forecasting in terms of MAPE. (2) It has been proven that our proposed CNN–Transformer model could achieve more outstanding forecasting performance. Compared with the CEEMDAN-VMD-CNN, the CEEMDAN-VMD-CNN–Transformer method declined by 13.58%, 11.88% and 11.10% in three-step-ahead forecasting in terms of MAPE.

Cross-Domain Person Re-Identification Based on Feature Fusion Invariance

Cross-domain person re-identification is a technique for identifying the same individual across different cameras or environments that necessitates the overcoming of challenges posed by scene variations, which is a primary challenge in person re-identification and a bottleneck for its practical applications. In this paper, we learn the invariance model of cross-domain feature fusion in a labeled source domain and an unlabeled target domain. First, our method learns the global and local fusion features of a person in the source domain by means of supervised learning with no component label and only person identification and obtains the fusion features of the person in the source and target domains by means of unsupervised learning. Based on person fusion features, this paper introduces feature memory to store the fused target features and designs a cross-domain invariance loss function to improve the cross-domain adaptability of the person. Finally, this paper carries out cross-domain person re-identification verification experiments between the Market-1501 and DukeMTMC-reID datasets; the experimental results show that the proposed method achieves significant performance improvement in cross-domain person re-identification.

Performance reliability evaluation of high‐pressure internal gear pump

AbstractWith the development of the high‐end equipment technology, the performance requirements of the internal gear pump (IGP) under high pressure are also increasing. However, the increase of working pressure will lead to the instability of gear pump performance in terms of volumetric efficiency, noise, reliability and so on, it is necessary to reasonably evaluate the reliability level of high‐pressure IGP. The reliability analysis of the high‐pressure IGP is carried out from the aspects of flow, noise, and gear strength in this paper. First, the output flow rate and far‐field flow‐induced noise of the high‐pressure IGP were obtained through fluid numerical simulation, and experimental verification was conducted. Then, based on the time‐varying meshing stiffness, backlash function and static transmission error of the gear pair, a nonlinear dynamic model of the internal meshing gear pair was established. The time‐varying meshing force was obtained through the dynamic model of the gear pair, and then the tooth contact stress and tooth root bending stress were obtained. Finally, considering the uncertain factors affecting the performance of the high‐pressure IGP, Latin hypercube sampling (LHS) combined with dendrite network (DD) was used for random response modeling. The performance reliability of the high‐pressure IGP, including output flow rate, far‐field flow‐induced noise, and the strength of gear pair, were estimated based on the fourth moment‐based saddlepoint approximation (FMSA). The reliability analysis results can provide a theoretical basis for the structural optimization design of the high‐pressure IGP.

Fano resonance in one-dimensional quasiperiodic topological phononic crystals towards a stable and high-performance sensing tool

Phononic crystals (PnCs) emerge as an innovative sensor technology, especially for high-performance sensing applications. This study strives to advance this field by developing new designs of PnC structures that exhibit stability in the face of construction imperfections and deformations, focusing on the evolution of topological PnCs (TPnCs). These designs could be promising to overcome the problem of instability involved in most of the theoretical PnC sensors when they emerge in experimental verification. In particular, the fabrication process of any design could collide with some fluctuations in controlling the size of each component. Thus, Fano resonance is introduced through a one-dimensional (1D) quasiperiodic TPnC. To the best of the author’s knowledge, this study is the first to observe Fano modes in liquid cavities through 1D PnCs. Various quasiperiodic PnC designs are employed to detect the temperature of alcohols (specifically propanol) across an extensive temperature range (160–240 °C). The effects of many geometrical parameters on the sensor stability, such as material thicknesses, are studied. Numerical findings demonstrated that the designed quasiperiodic topological PnCs based on Fibonacci sequence of the second order proved superior performance. This sensing tool provides sensitivity, quality factor and figure-of-merit values of 104,533.33 Hz/°C, 223.69 and 0.5221 (/°C), respectively, through temperature detection of propanol in the range of 160–240 °C.

Transcriptomic characteristics analysis of bone from chronic osteomyelitis

To explore the molecular mechanism of chronic osteomyelitis and to clarify the role of MAPK signal pathway in the pathogenesis of chronic osteomyelitis, by collecting and analyzing the transcriptional information of bone tissue in patients with chronic osteomyelitis. Four cases of traumatic osteomyelitis in limbs from June 2019 to June 2020 were selected, and the samples of necrotic osteonecrosis from chronic osteomyelitis (necrotic group), and normal bone tissue (control group) were collected. Transcriptome information was collected by Illumina Hiseq Xten high throughput sequencing platform, and the gene expression in bone tissue was calculated by FPKM. The differentially expressed genes were screened by comparing the transcripts of the Necrotic group and control group. Genes were enriched by GO and KEGG. MAP3K7 and NFATC1 were selected as differential targets in the verification experiments, by using rat osteomyelitis animal model and immunohistochemical analysis. A total of 5548 differentially expressed genes were obtained by high throughput sequencing by comparing the necrotic group and control group, including 2701 up-regulated and 2847 down-regulated genes. The genes enriched in MAPK pathway and osteoclast differentiation pathway were screened, the common genes expressed in both MAPK and osteoclast differentiation pathway were (inhibitor of nuclear factor κ subunit Beta, IκBKβ), (mitogen-activated protein kinase 7, MAP3K7), (nuclear factor of activated t cells 1, NFATC1) and (nuclear factor Kappa B subunit 2, NFκB2). In rat osteomyelitis model, MAP3K7 and NFATC1 were highly expressed in bone marrow and injured bone tissue. Based on the transcriptome analysis, the MAPK signaling and osteoclast differentiation pathways were closely related to chronic osteomyelitis, and the key genes IκBKβ, MAP3K7, NFATC1, NFκB2 might be new targets for clinical diagnosis and therapy of chronic osteomyelitis.

Bioinformatics analysis and experimental verification of the cancer-promoting effect of DHODH in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the urinary system. To explore the potential mechanisms of DHODH in ccRCC, we analyzed its molecular characteristics using public databases. TCGA pan-cancer dataset was used to analyze DHODH expression in different cancer types and TCGA ccRCC dataset was used to assess differential expression, prognosis correlation, immune infiltration, single-gene, and functional enrichment due to DHODH. The GSCALite and CellMiner databases were employed to explore drugs and perform molecular docking analysis with DHODH. Protein–protein interaction networks and ceRNA regulatory networks of DHODH were constructed using multiple databases. The effect of DHODH on ccRCC was confirmed in vitro. DHODH was highly expressed in ccRCC. Immune infiltration analysis revealed that DHODH may be involved in regulating the infiltration of immunosuppressive cells such as Tregs. Notably, DHODH influenced ccRCC progression by forming regulatory networks with molecules, such as hsa-miR-26b-5p and UMPS and significantly enhanced the malignant characteristics of ccRCC cells. Several drugs, such as lapatinib, silmitasertib, itraconazole, and dasatinib, were sensitive to DHODH expression and exhibited strong molecular binding with it. Thus, DHODH may promote ccRCC progression and is a candidate effective therapeutic target for ccRCC.

Secure transmission in a W-band RoF system based on delta-sigma modulation

In this Letter, a delta-sigma modulation (DSM) encryption technique in a W-band RoF system is proposed. By performing DSM with different over-sample ratios (OSRs) on the OFDM signal based on the controlled keys generated by the chaotic system at the transmitter and performing constellation masking to disturb the transmitting signal for encryption, a high-order QAM-OFDM-DSM encrypted signal is achieved. In order to further improve the security of the system, bit bidirectional diffusion scrambling is used to resist chosen-plaintext attacks. After experimental verification, under the same transmission power, the encrypted DSM signal can achieve better security than single OSR of DSM signals through a 50-km standard single-mode fiber (SSMF) and a 3-m wireless channel, with the gain of sensitivity increased by ∼1 dBm. From the reliability of the system, the encrypted signal of the proposed scheme can be recovered, which meets a hard decision-forward error correction (HD-FEC) threshold of 3.8 × 10−3.

The Force–Frequency Characteristics of Quartz Wafers under a Cantilever Beam Structure

This study investigated the force–frequency characteristics of quartz wafers inside a cantilever beam frame. Firstly, the force–frequency coefficient formula of quartz wafers with fixed ends under axial force was analyzed. Firstly, the formula for the force–frequency coefficient of quartz wafers with fixed ends under axial force was analyzed. A force–frequency coefficient formula suitable for cantilever beam structures was derived by considering the changes in surface stress and stiffness of quartz wafers with fixed ends and one end under force on the other. Subsequently, the formula’s accuracy was verified by experiments, and the accuracy was more than 92%. In addition, strain simulation analysis was performed on three different shapes of quartz wafers, and experimental verification was carried out on two of them. The results revealed that trapezoidal quartz wafers and cantilever beam structures exhibited superior stress distribution to rectangular chips. Furthermore, by positioning electrodes at various locations on the surface of the quartz chip, it was observed that, as the electrodes moved closer to the fixed end, the force–frequency coefficient of the rectangular quartz chip increased, along with an increase in chip strain under the cantilever structure. In summary, this study provides a new approach for designing cantilever quartz resonator sensors in the future.

Freeform generative design of complex functional structures

Generative machine learning is poised to revolutionise a range of domains where rational design has long been the de facto approach: where design is practically a time consuming and frustrating process guided by heuristics and intuition. In this article we focus on the domain of flow chemistry, which is an ideal candidate for generative design approaches. We demonstrate a generative machine learning framework that optimises diverse, bespoke reactor elements for flow chemistry applications, combining evolutionary algorithms and a scalable fluid dynamics solver for in silico performance assessment. Experimental verification confirms the discovery of never-before-seen bespoke mixers whose performance exceeds the state of the art by 45%. These findings highlight the power of autonomous generative design to improve the operational performance of complex functional structures, with potential wide-ranging industrial applications.

Investigation of cathode properties of two-dimensional NbS2Cl2 for Li and Na-ion batteries using density functional theory

Exploring novel two-dimensional materials (2D) for electrode and electrochemical storage applications stands as a pivotal pursuit in advancing renewable energy technologies. While recent research has predominantly focused on anode materials, cathode materials have received comparatively lesser attention. This study delves into the potential cathode applications of the novel two-dimensional material NbS2Cl2 using density functional theory. Fundamental properties, encompassing electronic and thermodynamic attributes, were scrutinized to comprehend the material’s characteristics. Our investigation extended to examining the adsorption and diffusion properties of these electrode materials. Comprehensive calculations of mechanical and thermodynamic properties reaffirmed the stability of this system. Upon adsorption of Li/Na atoms, the conducting nature emerged, evident through charge density difference and projected density of states. Our findings notably reveal minimal diffusion barriers of 1.5 eV and 0.35 eV for Li and Na atoms. Moreover, the observed open circuit voltages for adsorbed Li and Na ions were 4.69 V and 2.62 V, respectively. The calculated theoretical capacity for adsorbed Li-ion on 2D-NbS2Cl2 is 400 mAh g−1, while for Na-ion adsorption, it is 353 mAh g−1, awaiting validation through future experimental verifications.

Application of Improved Ant Colony Algorithm in Optimizing the Charging Path of Electric Vehicles

In current traffic congestion scenarios, electric vehicles (EVs) have the problem of reduced battery life and continuous decline in endurance. Therefore, this study proposes an optimization method for electric vehicle charging scheduling based onthe ant colony optimization algorithm with adaptive dynamic search (ADS-ACO), and conducts experimental verification on it. The experiment revealed that in the four benchmark functions, the research algorithm has the fastest convergence speed and can achieve convergence in most of them. In the validation of effectiveness, the optimal solution for vehicle time consumption under the ADS-ACO algorithm in the output of the algorithm with a stationary period and a remaining battery energy of 15 kW·h was 2.146 h in the regular road network. In the initial results of 15 kW·h under changes in road conditions from peak to peak periods, the total energy consumption of vehicles under the research algorithm was 4.678 kW·h and 4.656 kW·h under regular and irregular road networks, respectively. The change results were 4.509 kW·h and 4.656 kW·h, respectively. The initial results of 10 kW·h were 4.755 kW·h and 4.873 kW·h, respectively. The change results were 4.461 kW·h and 4.656 kW·h, respectively, which are lower than the comparison algorithm. In stability verification, research algorithms can find the optimal path under any conditions. The algorithm proposed in the study has been demonstrated to be highly effective and stable in electric vehicle charging path planning. It represents a novel solution for electric vehicle charging management and is expected to significantly enhance the range of electric vehicles in practical applications.