Search

Vehicle driving cycles have complex characteristics, but there are few publicly reported methods for their quantitative characterization. This paper innovatively investigates their multifractal characteristics using the fractal theory to characterize their complex properties, laying the foundation for applications such as vehicle driving cycle feature identification, vehicle energy management strategies (EMS), and so on. To explore the scale-invariance of the vehicle driving cycles, the four vehicle driving cycles were analyzed using the Multifractal Detrended Fluctuation Analysis (MF-DFA) method, three of which are standard vehicle test cycles: the New European Driving Cycle (NEDC), the World-wide harmonized Light-duty Test Cycle (WLTC) and the China Light-duty Vehicle Test Cycle for Passenger Car (CLTC-P), and the other is the Urban Road Real Driving Cycle (URRDC), which was obtained by analyzing and processing vehicle driving data collected in actual urban driving conditions. The fluctuation functions, the generalized Hurst exponents, the mass exponent spectra, the multifractal singularity spectra, and the multifractal characteristic parameters were calculated to verify the multifractal characteristics, and to quantify the fluctuation singularities of different driving cycles as the time series. The results show that the fluctuations of all four driving cycles have long-range anticorrelations and exhibit significant multifractal characteristics. The results can provide a basis for the analysis of the complexity of the vehicle driving cycles.

Conventional hybrid vehicles with two energy sources require two separate on-board DC/DC converters to connect the battery and the fuel cell, which have the disadvantages of large size, high cost, high losses and few applicable operating conditions. To address this situation, this paper proposes an optimized on-board integrated DC/DC converter with a non-isolated multi-port scheme that integrates a unidirectional port for the fuel cell and a bidirectional port for the battery and load. This can achieve a combined energy supply and recovery with a single integrated converter, effectively overcoming the above disadvantages. The optimized converter topology is relatively simple, and the magnetic losses of the transformer are removed. Furthermore, the switched capacitor is introduced as a voltage doubling unit to achieve high-gain output, so the fuel cell and battery voltage demand levels are reduced under the same load conditions. In addition, it has superior performance in system energy management for hybrid vehicles, which can distribute power and switch operating states by controlling the on/off of switching devices to make it suitable for five driving conditions. This paper discusses in detail the operating principles of the converter and analyzes its steady-state performance under five operating modes, derives its dynamic model, and proposes a proportional-integral control scheme. Finally, the simulation model of the topology is built by Matlab/Simulink software to verify the converter operation in each driving state, and the simulation experimental results verify the applicability of the proposed integrated DC/DC converter topology.

Abstract Background Re-capture of the differences between tumor and normal tissues observed at the patient level in cell cultures and animal models is critical for applications of these cancer-related differences. The epithelial-mesenchymal transition (EMT) process is essential for tumor migratory and invasive capabilities. Although plenty of EMT markers are revealed, molecular features during the early stages of EMT are poorly understood. Methods A cell-based model to induce lung cell (A549) EMT using conditioned medium of in vitro cancer activated fibroblast (WI38) was established. High-throughput sequencing methods, including RNA-seq and miRNA-seq, and advanced bioinformatics methods were used to explore the transcriptome profile transitions accompanying the progression of EMT. We validated our findings with experimental techniques including transwell and immunofluorescence assay, as well as the TCGA data. Results We have constructed an in vitro cell model to mimic the EMT in patients. We discovered that several new transcription factors were among the early genes (3 h) to respond to cancer micro-environmental cues which could play critical roles in triggering further EMT signals. The early EMT markers also included genes encoding membrane transporters and blood coagulation function. Three of the nine-examined early EMT hallmark genes, GALNT6, SPARC and HES7, were up-regulated specifically in the early stages of lung adenocarcinoma (LUAD) and confirmed by TCGA patient transcriptome data. In addition, we showed that miR-3613, a regulator of EGFR pathway genes, was constantly repressed during EMT progress and indicative of an epithelial miRNA marker. Conclusions The CAF-stimulated EMT cell model may recapture some of the molecular changes during EMT progression in clinical patients. The identified early EMT hallmark genes GALNT6, SPARC and HES7and miR-3613 provide new markers and therapeutic targets for LUAD for the further clinical diagnosis and drug screening.

Excellent thermoelectric materials need both high carrier transport properties and low phonon transport properties simultaneously, which make it challenging to enhance thermoelectric performance. However, recent progress shows that sub-nanostructures can strongly intensify phonon scattering but scarcely impede carrier mobility, thus effectively contributing to high thermoelectric performance in PbTe/Se-based systems. In this perspective, we summarize the thermoelectric transport properties and internal atomic-scale structures in these PbTe/Se-based systems with sub-nanostructures. Then, their thermoelectric properties are comprehensively compared with other massively nanostructured PbTe/Se-based systems, reveling the favorable role of sub-nanostructures in achieving high carrier mobility. Finally, several other potential strategies to further maintain carrier transport properties and enhance thermoelectric performance are proposed, which might be extended to other thermoelectric systems.

An improved RRT∗ algorithm, referred to as the AGP-RRT∗ algorithm, is proposed to address the problems of poor directionality, long generated paths, and slow convergence speed in multi-axis robotic arm path planning. First, an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency. Second, a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to accelerate the search speed of the algorithm. Finally, the planning path is processed by pruning, removing redundant points and path smoothing fitting using cubic B-spline curves to improve the flexibility of the robotic arm. Through the six-axis robotic arm path planning simulation experiments on the MATLAB platform, the results show that the AGP-RRT∗ algorithm reduces 87.34% in terms of the average running time and 40.39% in terms of the average path cost; Meanwhile, under two sets of complex environments A and B, the average running time of the AGP-RRT∗ algorithm is shortened by 94.56% vs. 95.37%, and the average path cost is reduced by 55.28% vs. 47.82%, which proves the effectiveness of the AGP-RRT∗ algorithm in improving the efficiency of multi-axis robotic arm path planning. [ABSTRACT FROM AUTHOR]

Thermoelectric cooling technology has important applications for processes such as precise temperature control in intelligent electronics. The bismuth telluride (Bi2Te3)-based coolers currently in use are limited by the scarcity of Te and less-than-ideal cooling capability. We demonstrate how removing lattice vacancies through a grid-design strategy switched PbSe from being useful as a medium-temperature power generator to a thermoelectric cooler. At room temperature, the seven-pair device based on n-type PbSe and p-type SnSe produced a maximum cooling temperature difference of ~73 kelvin, with a single-leg power generation efficiency approaching 11.2%. We attribute our results to a power factor of ‘52 microwatts per centimeter per square kelvin, which was achieved by boosting carrier mobility. Our demonstration suggests a path for commercial applications of thermoelectric cooling based on Earth-abundant Te-free selenide-based compounds. [ABSTRACT FROM AUTHOR]