纯电动汽车能耗经济性评价方法研究

在纯电动汽车能耗经济性评价指标分析基础上,建立了加速、匀速、减速、驻车四种不同行驶工况下纯电动汽车能耗经济性计算的数学模型.基于实验测试分析了环境温度对能耗的影响,得到了不同环境温度下电动汽车能耗经济性变化规律.最后以纯电动公交客车为例,对加速-滑行组合工况下能耗经济性进行了分析计算,验证了能耗经济性分析数学模型的可行性.     

A Multi-Objective Decision-Making Approach for the Optimal Location of Electric Vehicle Charging Facilities

Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the dual objectives. On the basis of satisfying the user’s charging demand and the capacity constraints of EVCSs, the redundant design of the charging pile and station is considered to ensure the reliability of the service network. In the allocation of user charging demand, in this paper, two factors of time and distance are considered, and the equal time load distance method is adopted to distribute traffic flow under the limitation of emergency charging mileage. When calculating the average travel speed of a road section, an accounting method based on the land price level is proposed considering the congestion. Then, the linear weighting method is applied to normalizing the multi-objective function, and the genetic algorithm is employed to solve the problem. Finally, a computational experiment is presented to demonstrate the applicability and effectiveness of the proposed approach. The results show that the proposed approach is a useful, practical, and effective way to find the optimal location of EVCSs.     

Performance evaluation of a vapor injection heat pump system for electric vehicles

Battery-powered electric vehicles (EV) need an efficient electric heating system for extending the driving mileage. An air-source heat pump system offers an economical alternative for EV because it consumes less energy than a heating system using Joule heat and it can use the same components as an air conditioning system for cooling. However, its performance degradation is inevitable at very low ambient temperatures. Although vapor refrigerant injection is known as a good technology to overcome this problem in residential heat pump systems, the number of vapor injection heat pump studies for EV applications is quite limited. In this paper, considering the characteristics of EV application, the configuration of a vapor injection heat pump system for EV is introduced, and it was modeled, using a scroll compressor geometry-based thermodynamic analysis. The performance was estimated for cold ambient regions under the EV operational conditions.     

纯电动汽车冬季冷启动阶段热管理策略影响续驶里程分析

针对纯电动汽车冬季续驶里程严重衰减的问题,本文通过建立以电池产热、空调负荷为参数的汽车续驶里程数学模型,仿真分析冬季冷启动时,美国高速公路燃料经济性测试工况(HWFET)、新欧洲行驶工况(NEDC)、中国乘用车行驶工况(CLTC-P)三种行驶工况下热泵供暖及环境温度(AT)、舱内温度(CT)对整车续驶里程和车载电池的影响。经与实测数据进行对比,仿真与实验匹配度较好。研究结果表明:三种工况下,AT下降、CT上升均使续驶里程逐渐衰减;AT为0℃,CT为15、20、25℃时,CLTC-P工况续驶里程分别衰减21.46%、27.74%、33.19%;纯电动汽车冷启动时,三种热量分配策略对续驶里程影响不同,当热泵热量全部用于加热电池时能适当恢复电池电量,在NEDC和CLTC-P工况下,电池最大荷电状态(SOC)相比初始SOC增加了1.52%、2.03%,使用热泵能增加一定的续航里程。     

Electric vehicle scheduling and optimal charging problem: complexity,exact and heuristic approaches

This paper deals with the Electric Vehicle (EV) Scheduling and Optimal Charging Problem. More precisely, given a fleet of EVs and Combustion Engine Vehicles (CVs), a set of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimise the assignment of vehicles to tours and minimise the charging cost of EVs while considering several operational constraints mainly related to chargers, electricity grid and EVs driving range. We prove that the Electric Vehicle Scheduling and Charging Problem (EVSCP) is NP-hard in the ordinary sense. We provide a mixed-integer linear programming formulation to model the EVSCP and use CPLEX to solve small and medium instances. To solve large instances, we propose two heuristics: a Sequential Heuristic (SH) and a Global Heuristic (GH). The SH considers the EVs sequentially. To each EV, it assigns a set of tours and guarantees the feasibility of a charging schedule. Then, it generates an optimal charging schedule for this EV. However, the GH computes, in the first step, a feasible assignment of tours to all EVs. In the second step, it applies a global Min-Cost-Flow-based charging algorithm to minimise the charging cost of the EVs fleet. To evaluate the efficiency of our solving approaches, computational results on a large set of real and randomly generated test instances are reported and compared.     

基于改进HMM和Pearson相似度分析的滚动轴承自适应寿命预测方法

基于数据驱动思想,提出了一种相同工况下的滚动轴承寿命预测方法。针对轴承全寿命监测数据,根据K-means聚类算法划分轴承运行状态空间,考虑到隐马尔科夫模型主链为状态链的不足,对状态转移矩阵重新定义,将主链改进为寿命链,建立了基于改进HMM的全寿命状态驻留时间模型;将观测轴承数据、实时与建模数据进行Pearson相似度分析,构造寿命比例调节系数,实现寿命模型参数的动态修正和观测轴承寿命的自适应预测。采用美国辛辛那提大学实验中心轴承试验数据开展了应用研究,通过一组轴承全寿命数据实现了对其它轴承不同阶段及全寿命的预测,与传统的隐马尔科夫模型、灰色模型预测等方法预测结果相比,所提算法兼具较好的预测准确性和模型的泛化性。     

Application of a small-timescale fatigue,crack-growth model to the plane stress/strain transition in predicting the lifetime of a tunnel-boring-machine cutter head

The crack-growth lifetime of a tunnel-boring-machine (TBM) cutter head accounts for more than 80% of a TBM cutter head's entire lifetime. Considering the ultrathick plate of a TBM cutter head, a small-timescale crack-growth model is modified to predict crack-growth lifetime based on the plane stress/strain transition condition. An improved quasistatic method is proposed to calculate the dynamic stress of the weak points of the cutter head, which is used as the input load. A plastic constraint factor α is introduced to change the yield stress value of the material. The transition of the stress/strain state in the crack tip is simulated, and the modified model is verified by a fatigue crack-growth test of the characteristic substructure, giving better prediction results. Finally, this method is applied to predict the crack-growth lifetime of a TBM cutter head in the Water Diversion Project in Northwest Liaoning Province, China, and the results show that when the crack of the cutter head's vulnerable part grows from 0.1 mm to 60 mm in depth, the TBM's useful driving distance is about 11.2 km.     

DNA-Guided Extracellular-Vesicle Metallization with High Catalytic Activity for Accurate Diagnosis of Pulmonary Nodules

Sensitive and specific analysis of extracellular vesicles (EVs) offers a promising minimally invasive way to identify malignant pulmonary nodules from benign lesions. However, accurate analysis of EVs is subject to free target proteins in blood samples, which compromises the clinical diagnosis value of EVs. Here a DNA-guided extracellular-vesicle metallization (DEVM) strategy is described for ultrasensitive and specific analysis of EV protein biomarkers and classification of pulmonary nodules. The facile DEVM process mainly includes the incorporation of DNA labeled with cholesterol and thiol groups into EV membranes and subsequent deposition of Au³⁺ and Pt⁴⁺ to allow the DNA-functionalized EVs to be encapsulated with AuPt nanoshells. It is found that the synthesized AuPt-metallized EVs possess extrinsic peroxidase-like activity. Utilizing the feature of the catalytic metal nanoshells just growth on the EV membranes, the DEVM method enables multiparametric recognition of target proteins and EV membranes and can produce an amplified colorimetric signal, avoiding the interference of free proteins. By profiling four surface proteins of EVs from 48 patients with pulmonary nodules, the highest area under the receiver operating characteristic curve (0.9983) is obtained. Therefore, this work provides a feasible EVs analysis tool for accurate pulmonary nodules management.     

Verformungsverhalten und rechnerische Abschätzung der Ermüdungslebensdauer metallischer Werkstoffe unter mehrachsig nichtproportionaler Beanspruchung

Deformation behaviour and numerical fatigue lifetime prediction of metallic materials under multiaxial nonproportional loading The development and evaluation of a model for lifetime prediction under multiaxial nonproportional loading is the aim of the current research project. It is assumed that the technical crack initiation life is consumed by short crack growth. This phenomenon is described using a fracture mechanics based approach. Herein, the effective cyclic J‐integral is used as crack tip parameter. Crack opening levels and J‐integral values are calculated applying approximation formulas. A plasticity model that is based on the Jiang model [Jia93] and extended to describe nonproportional hardening is used to predict the deformation behaviour. Experimental investigations on tubular and notched specimens with a wide range of different loading spectra serve for the verification of the model and for the identification of damage mechanisms.     

Utilizing Accelerated Degradation and Field Data for Life Prediction of Highly Reliable Products

For newly developed, highly reliable, and long‐lifespan products, it is quite difficult to implement effective remaining useful life (RUL) prediction in the early usage under limited time cost. However, accelerated degradation testing (ADT) is generally used for lifetime evaluation for such products with harsher test conditions and shorter test time in the late research and development phase. Thus, in this paper, we propose a life prediction framework to integrate the information from ADT to conduct field RUL prediction for highly reliable products. Because ADT belongs to reliability testing used for inferring the population information from the selected test samples, we at first present the modified Wiener process (MWP) model. Different from traditional methods that embody both the random variability and unit‐to‐unit variability into the diffusion coefficient, the proposed method describes them separately in ADT analysis. Then, the MWP model from ADT is used as a prior for field RUL prediction of the target product during which the strong tracking filtering algorithm is introduced for updating the hidden state and computing the RUL prediction results when the new monitoring data are available. Because of the complexity of the MWP model, the Markov chain Monte Carlo method is provided to estimate the unknown parameters. Finally, the simulation study and the light‐emitting diode application verify the effectiveness of the proposed framework that can achieve reasonable life prediction results for highly reliable products for both linear and nonlinear scenarios. Copyright © 2015 John Wiley & Sons, Ltd.     

Physics of failure-based degradation modeling and lifetime prediction of the momentum wheel in a dynamic covariate environment

We consider the problem of reliability modeling and evaluation of the Momentum Wheel (MW) in long-life satellites under small sample circumstances, proposing a physics-of-failure-based degradation model and life prediction method for such MWs in a dynamic covariate environment. From the results of a physics of failure experiment, we first derive models for the distribution and microcirculation of bearing lubricant. Next, we identify the qualitative and quantitative relationships between the key factors, e.g. rotation speed and bearing temperature, and the loss of lubricant. Then, taking the bearing temperature as a dynamic covariate, we build a degradation model for lubricant loss in the bearing assembly that corresponds to a Wiener process with drift that is positively associated with the covariate. To estimate the parameters of this degradation model, we use the method of maximum likelihood and the data from the physics of failure experiment. To predict the lifetime of an individual MW under orbital conditions, we suggest using Empirical Mode Decomposition (EMD) and regression analysis to model the trend in bearing temperature derived from telemetry data. Bootstrap simulation provides a satisfactory way of coping with the various sources of uncertainty in our prediction. Based on the predicted bearing temperature and the lubricant loss model, we estimate the amount of lubricant lost by an individual MW bearing, and hence obtain the lifetime of the lubrication system by comparing the predicted values for residual lubricant with the designed lubricant capacity. A case study involving data from a particular type of MW demonstrates the merits of this lifetime prediction method that we propose.     

Research on lease and sale of electric vehicles based on value engineering

Electric vehicles (EVs) acknowledged as potential means of transportation tools in the near future are widely accepted as the development trend of automobile industry due to its environment protection and fuel energy saving properties. As a product containing new technologies and concepts with little market experience and consumer identification, studying its life cycle operation modes will help to figure out an optimal approach to conduct EVs manufacturing and service. The two common operation modes, lease and sale of EVs, have their own advantages and weaknesses under different scenarios and consumer psychological status. Research and comparisons on the function, cost and value of two operation modes in full life cycle will simulate the rapid development of EVs forming a mature and dynamic operation mechanism. This paper utilised approaches in value engineering, putting forward customer requirements and technical elements of EV lease and sale based on quality assessment and customer-perceived value, proposing the metric method of function and cost coefficient by mathematical modelling, and conducting value coefficient analysis and comparison based on customer’s risk aversion psychology. An illustrative example raised for studying operation mode of three different kinds of EVs based on the analysis of value coefficient, providing guideline for manufacturer and servicers of EVs.     

Is rigorous punishment effective? A case study of lifetime license revocation in Taiwan

This study investigated the effectiveness of administrative lifetime driver's license revocation (ALLR) and its impact on offenders, based on a two-stage survey of 768 offenders. It was found that after ALLR had been imposed, 23.4% of these offenders were still driving almost the same as before, 59.8% drove significantly less frequently, and only 16.8% of the offenders gave up driving completely. The results of logistic regression models showed that offenders' compliance with ALLR was significantly correlated with their personal characteristics (age, income), penalty status (incarceration, duration of ALLR), and the need to drive for working, commuting and shopping. Elderly and low-income offenders were more likely to abide by the ALLR restriction. The application of the generalized estimating equations (GEE) model was used to identify the determinant factors affecting offenders' driving mileage, and to effectively estimate the driving mileage reduction as a result of the ALLR. It was found that ALLR is fairly effective in keeping offenders off the road, but that it may reduce their ability to make a living, resulting in the less fortunate becoming more helpless.     

Empirical model of roughness effect on vehicle speed

Vehicle speed–roughness relationship has a significant research gap in life cycle assessment model. The current available models describing the roughness effect on vehicle speed are very limited and outdated. In this paper, 32 individual pavement sections, each of which has roughness data of up to 8 years, were selected to develop the model. The roughness data cover a wide range, and the selected pavement sections contain both flexible and rigid pavement types and various numbers of lanes. Involved regression variables include the following: vehicle speed, roughness, volume–capacity ratio, pavement type, number of lanes and speed limit. Analysis of variance was first performed, indicating that pavement type and speed limit are not significant factors influencing the average vehicle speed. Following, strict statistical technique was used to correct the unobserved heterogeneity during the regression using a one-way fixed random model. The obtained regression model reveals that the average vehicle speed decreases 0.0083 mph with every 1 in/mi increase of the roughness ( ? 0.84 km/h per m/km).     

Label-Free Identification of Exosomes using Raman Spectroscopy and Machine Learning

Exosomes, nano-sized extracellular vesicles (EVs) secreted from cells, carry various cargo molecules reflecting their cells of origin. As EV content, structure, and size are highly heterogeneous, their classification via cargo molecules by determining their origin is challenging. Here, a method is presented combining surface-enhanced Raman spectroscopy (SERS) with machine learning algorithms to employ the classification of EVs derived from five different cell lines to reveal their cellular origins. Using an artificial neural network algorithm, it is shown that the label-free Raman spectroscopy method's prediction ratio correlates with the ratio of HT-1080 exosomes in the mixture. This machine learning-assisted SERS method enables a new direction through label-free investigation of EV preparations by differentiating cancer cell-derived exosomes from those of healthy. This approach will potentially open up new avenues of research for early detection and monitoring of various diseases, including cancer.     

复杂面内应力状态下平面编织高铝纤维增强氧化铝基复合材料强度及疲劳寿命预测方法

针对平面编织氧化铝基复合材料提出了一种复杂面内应力状态下的强度准则和疲劳寿命预测方法。通过拉伸、压缩及纯剪切试验,分别获得了材料的静强度指标。考虑材料拉、压性能的差异和面内拉-剪联合作用对材料强度的影响机制,提出了修正的Hoffman强度理论。采用该强度理论预测得到的偏轴拉伸强度与试验结果基本一致,偏差不超过10%。开展了偏轴角θ=0°、15°、30°、45°,应力比R=0.1,频率f=10 Hz的拉伸疲劳试验,试验结果表明随着偏轴角的增加,相同轴向拉伸载荷下的疲劳寿命逐渐降低。由于面内剪切应力分量的作用,疲劳失效由纤维主导逐渐过渡到纤维和基体共同主导的模式。基于单轴疲劳寿命曲线,采用Broutman-Sahu剩余强度模型表征剩余强度随疲劳循环次数的变化规律,结合剩余强度演化模型和修正的Hoffman强度理论,提出了一种面内复杂载荷条件下的疲劳寿命预测模型,并引入疲劳剪切损伤影响因子表征拉-剪应力联合作用对材料疲劳行为的影响。采用本文提出的疲劳寿命预测模型,预测不同偏轴角拉伸疲劳寿命,预测结果与试验结果基本一致,偏差在1倍寿命范围内。比较结果表明在给定应力比、温度和疲劳载荷频率条件下,该疲劳寿命预测模型可以用来预测平面编织氧化铝基复合材料拉-剪复杂面内载荷条件下疲劳寿命。      

复合材料层合板冲击后压-压疲劳寿命预测方法

针对冲击后复合材料层合板, 发展了含冲击初始损伤层合板的压-压疲劳寿命预测方法。该方法基于无损单向板的力学性能和疲劳特性, 对不同铺层参数、 不同几何尺寸以及不同冲击条件下层合板的疲劳寿命进行预测。为消除人为假设冲击损伤造成的误差, 对层合板在冲击载荷及冲击后疲劳载荷作用下的破坏进行全程分析, 即把冲击后层合板的实际损伤状态直接作为疲劳分析的初始状态。同时基于逐渐损伤思想, 推导了含冲击初始损伤层合板的应力分析过程, 建立了相应的三维逐渐累积损伤模型, 开发了参数化的复合材料层合结构冲击及冲击后疲劳破坏模拟程序, 为复合材料层合结构的抗冲击设计及其疲劳损伤扩展行为研究提供了较好的技术平台。      

Generalisation of the concept of electronic differential

In this paper, we present a 3 degree-of-freedom dynamic model of a four-wheel-drive and four-wheel-steering electric vehicle (EV), which, instead of a complex mechanical transmission system, is equipped with an adequate controller known as electronic differential (ED). This ED distributes torque and power to each motor according to the requirements, adapts the speed of each motor to the driving conditions and simulates the behaviour of a differential. The most important advantages of this design-concept are simplicity, reduction of the mass of the EV and increase of the range of operation with one battery charge. Preliminary numerical results prove the viability of this design-concept.     

Driver perceptions of the safety implications of quiet electric vehicles

Previous research on the safety implications of quiet electric vehicles (EVs) has mostly focused on pedestrians’ acoustic perception of EVs, and suggests that EVs are more difficult for pedestrians to hear and, therefore, compromise traffic safety. The two German field studies presented here examine the experiences of 70 drivers with low noise emissions of EVs and the drivers’ long-term evaluation of the issue. Participants were surveyed via interviews and questionnaires before driving an EV for the first time, after 3 months of driving, and in the first study, again after 6 months. Based on participants’ reports, a catalogue of safety-relevant incidents was composed in Study 1. The catalogue revealed that low noise-related critical incidents only rarely occur, and mostly take place in low-speed environments. The degree of hazard related to these incidents was rated as low to medium. In Study 1, driver concern for vulnerable road users as a result of low noise diminished with increasing driving experience, while perceived comfort due to this feature increased. These results were replicated in Study 2. In the second study, it was additionally examined, if drivers adjust their perceived risk of harming other road users over time. Results show that the affective assessment of risk also decreased with increased driving experience. Based on individual experience, drivers adjust their evaluation of noise-related hazards, suggesting that dangers associated with low noise emissions might be less significant than previously expected.     

Prediction of turn down warping during hot plate rolling based on a Gaussian function

Turn down warping is a shape defect observed at the front end of a plate during hot rolling. To produce a flat plate without warping, a precise prediction of turn down warping is essential to achieve optimal control. Therefore, we propose a model based on a Gaussian function to predict turn down warping. The model uses the results from numerical analyses of hot plate rolling. The finite element code MARC was used for the numerical analysis. Hot plate rolling processing parameters, such as roll diameter, plate dimension, rolling speed, and pass line were all considered in the model. To verify the accuracy of the prediction model, the numerical results obtained by FEM were confirmed with data measured during industrial hot plate rolling. For the actual measurements of turn down warping, image processed high speed camera data from the exit side of the rolling were used. The results show that the proposed Gaussian function model can successfully predict turn down warping of a plate’s front end under various hot plate rolling conditions.