Planning of Electric Vehicle Charging Facilities on Highways Based on Chaos Cat Swarm Simulated Annealing Algorithm

Aiming at the layout planning of electric vehicle (EV) charging facilities on highways, this study builds a multi-objective optimization model with the minimum construction cost of charging facilities, minimum access cost to the grid, minimum operation and maintenance cost, and maximum carbon emission reduction benefit by combining the state of charge (SOC) variation characteristics and charging demand characteristics of EVs. A chaos cat swarm simulated annealing (CCSSA) algorithm is proposed. In this algorithm, chaotic logistic mapping is introduced into the cat swarm optimization (CSO) algorithm to satisfy the planning demand of EV charging facilities. The location information of the cat swarm is changed during iteration, the search mode and tracking mode are improved accordingly. The simulated annealing method is adopted for global optimization search to balance the whole swarm in terms of local and global search ability, thus obtaining the optimal distribution strategy of charging facilities. The case of the Xi’an highway network in Shanxi Province, China, shows that the optimization model considering carbon emission reduction benefits can minimize the comprehensive cost and balance economic and environmental benefits. The facility spacing of the obtained layout scheme can meet the daily charging demand of the target road network area

Resonance characteristics analysis of the power reflux hydraulic transmission system

The power reflux hydraulic transmission system (PRHTS), which is a new continuously variable transmission system, is put forward to enhance the efficiency of the torque converter. This study shows that the basic structure and operating principle of the PRHTS. Because the six-cylindered diesel engine’s operation range is between 40 Hz and 150 Hz, resonance point of the PRHTS should not exist in resonance region of engine. In order to study the resonance characteristics of the PRHTS, the dynamic model of the PRHTS is established by merging the planetary gear train dynamic model and torque converter dynamic model. This study also researches the amplitude-frequency characteristic curves of the PRHTS with different speed ratio and the effect of the torsional stiffness and damping coefficient to the amplitude-frequency characteristic of the PRHTS. The simulation result shows that the resonance frequency of the PRHTS could be excluded from engine’s operation range and the amplitude will decrease by changing the torsional stiffness and damping coefficient of the coupling

Fuzzy-Bayesian-network-based Safety Risk Analysis in Railway Passenger Transport

This study presents a fuzzy Bayesian network (FBN) method to analyze the influence on the safety risk of railway passenger transport applying different risk control strategies. Based on the fuzzy probability of the basic event determined by the expert group decision method, the proposed FBN method can reasonably predict the probability of railway passenger safety risk. It is also proven that control the risk in the safety management of railway passenger transport will be the most effective way to reduce the risk probability of the railway passenger transport safety

Optimization Model of Taxi Fleet Size Based on GPS Tracking Data

reasonable taxi fleet size has a significant impact on the satisfaction of urban traffic demand, the alleviation of urban traffic congestion, and the stability of taxi business groups. Most existing studies measure the overall scale by using macro indices, and few studies are from the micro level. To meet the transportation demand for taxis, mitigating the mismatch between taxi supply and demand, this research proposes an urban taxi fleet size calculating model based on GPS tracking data. Firstly, on the basis of road network segmentation, the probability model of a passenger taxi-taking a road section as a unit is built to evaluate the difficulty of taxi-taking on a road section. Furthermore, a user queuing model is built for the &ldquo difficult to take a taxi&rdquo road section in the peak period, and the service mileage required by potential taxi users is calculated. After that, a transportation capacity measurement model is built to estimate the number of taxis required in different time periods, Finally, the income constraint model is used to explain the impact of different vehicle fleet sizes on the income of taxi groups, so as to provide a reference for the determination of the final fleet size. The model is applied to data from Xi&rsquo an. The calculation results are based on data from May 2014, and show that the scale of taxi demand is about 654&ndash 2237, and after considering the impact of different fleet size increases on income, when the income variation index is limited to 0.10, i.e., the decrease of drivers&rsquo income will not exceed 10%, an increase of 1286 taxis will be able to meet 66% of the unmet demand in the peak period. The conclusion indicates that the model can effectively calculate the required fleet size and formulate the constraint solutions. This method provided can be considered as a support for formulating the regulation strategy of an urban taxi fleet size. Document type: Articl

Efficient removal of Cd(II) from aqueous solution by pinecone biochar: Sorption performance and governing mechanisms

Cadmium (Cd) is one of the most harmful and widespread environmental pollutants. Despite decades-long research efforts, the remediation of water contaminated by Cd has remained a significant challenge. A novel carbon material, pinecone biochar, was previously hypothesized to be a promising adsorbent for Cd, while so far, it has received little attention. This study evaluated the sorption capacity of pinecone biochar through isotherm experiments. Based on Langmuir model, the adsorption maximum for Cd(II) was up to 92.7 mg g−1. The mechanism of Cd(II) adsorption on pinecone biochar was also explored through both thermodynamic and kinetics adsorption experiments, as well as both solution and solid-phase microstructure characterization. The solid-solution partitioning behaviour of Cd(II) fitted best with the Tόth model while the adsorption process followed a pseudo-second-order rate, suggesting that the Cd(II) adsorption on the pinecone biochar was mainly a chemisorption process. Microstructure characteristics and mechanism analysis further suggested that coprecipitation and surface complexation were the main mechanisms of Cd adsorption by biochar. Coprecipitation occurred mainly through the forms of Cd(OH)2 and CdCO3. Our results demonstrated that pinecone biochar was an efficient adsorbent which holds a huge potential for Cd(II) removal from aqueous solution

A Novel Docetaxel-Loaded Poly (ε-Caprolactone)/Pluronic F68 Nanoparticle Overcoming Multidrug Resistance for Breast Cancer Treatment

Multidrug resistance (MDR) in tumor cells is a significant obstacle to the success of chemotherapy in many cancers. The purpose of this research is to test the possibility of docetaxel-loaded poly (ε-caprolactone)/Pluronic F68 (PCL/Pluronic F68) nanoparticles to overcome MDR in docetaxel-resistance human breast cancer cell line. Docetaxel-loaded nanoparticles were prepared by modified solvent displacement method using commercial PCL and self-synthesized PCL/Pluronic F68, respectively. PCL/Pluronic F68 nanoparticles were found to be of spherical shape with a rough and porous surface. The nanoparticles had an average size of around 200 nm with a narrow size distribution. The in vitro drug release profile of both nanoparticle formulations showed a biphasic release pattern. There was an increased level of uptake of PCL/Pluronic F68 nanoparticles in docetaxel-resistance human breast cancer cell line, MCF-7 TAX30, when compared with PCL nanoparticles. The cytotoxicity of PCL nanoparticles was higher than commercial Taxotere®in the MCF-7 TAX30 cell culture, but the differences were not significant (p > 0.05). However, the PCL/Pluronic F68 nanoparticles achieved significantly higher level of cytotoxicity than both of PCL nanoparticles and Taxotere®(p < 0.05), indicating docetaxel-loaded PCL/Pluronic F68 nanoparticles could overcome multidrug resistance in human breast cancer cells and therefore have considerable potential for treatment of breast cancer

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure &lt; 100 mmHg (n = 1127), estimated glomerular filtration rate &lt; 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Powertrain Matching and Optimization of Dual-Motor Hybrid Driving System for Electric Vehicle Based on Quantum Genetic Intelligent Algorithm

In order to increase the driving range and improve the overall performance of all-electric vehicles, a new dual-motor hybrid driving system with two power sources was proposed. This system achieved torque-speed coupling between the two power sources and greatly improved the high performance working range of the motors; at the same time, continuously variable transmission (CVT) was achieved to efficiently increase the driving range. The power system parameters were determined using the “global optimization method”; thus, the vehicle’s dynamics and economy were used as the optimization indexes. Based on preliminary matches, quantum genetic algorithm was introduced to optimize the matching in the dual-motor hybrid power system. Backward simulation was performed on the combined simulation platform of Matlab/Simulink and AVL-Cruise to optimize, simulate, and verify the system parameters of the transmission system. Results showed that quantum genetic algorithms exhibited good global optimization capability and convergence in dealing with multiobjective and multiparameter optimization. The dual-motor hybrid-driving system for electric cars satisfied the dynamic performance and economy requirements of design, efficiently increasing the driving range of the car, having high performance, and reducing energy consumption of 15.6% compared with the conventional electric vehicle with single-speed reducers

A highway crash risk assessment method based on traffic safety state division.

In order to quantitatively analyze the influence of different traffic conditions on highway crash risk, a method of crash risk assessment based on traffic safety state division is proposed in this paper. Firstly, the highway crash data and corresponding traffic data of upstream and downstream are extracted and processed by using the matched case-control method to exclude the influence of other factors on the model. Secondly, considering the weight of traffic volume, speed and occupancy, a multi-parameter fusion cluster method is applied to divide traffic safety state. In addition, the quantitative relationship between different traffic states and highway crash risk is analyzed by using Bayesian conditional logistic regression model. Finally, the results of case study show that different traffic safety conditions are in different crash risk levels. The highway traffic management department can improve the safety risk management level by focusing on the prevention and control of high-risk traffic safety conditions