Evaluating the reliability of distributed photovoltaic energy system and storage against household blackout

Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.

Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by cut-in.To improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic participants.The integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and trajectory.The dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference performance.Based on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax function.Finally,the comparative analysis is performed to validate the proposed method using the naturalistic driving data.The results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

Analysis and Optimization of Passenger Side Knee Slider Compression in Front Impact

The influences of different design factors,as well as dummy posture,on an occupants' knee slider compression,were studied in this paper.Based on the vehicle geometry data,the simulation model,including both the multi-rigid-body and finite element(FE)part,was built up and validated with China New Car Assessment Program(C-NCAP)full impact to ensure the accuracy of the model.By adjusting the design parameters and the posture of the femur and lower leg,different factors affecting the passengers' knee slider compression were evaluated,with the help of MAthematical DYnamic MOdel(MADYMO)simulations.The study indicated that the leg posture,the stiffness of the IP and angles of the carpet have significant effects on the knee slider compression in this case.By decreasing the angle between the femur and lower leg from 133° to 124°,the maximum knee slider compression was decreased by 17.3% and by scaling the IP stiffness from 1 to 0.7,it could be decreased by 18.6%.Also,decreasing the angles of the carpet from 28° to 37°can help reduce the knee slider compression by 18.3%.

Characterization and prediction of tailpipe ammonia emissions from in-use China 5/6 light-duty gasoline vehicles

On-road tailpipe ammonia (NH3) emissions contribute to urban secondary organic aerosol formation and have direct or indirect adverse impacts on the environment and human health. To understand the tailpipe NH3 emission characteristics, we performed comprehensive chassis dynamometer measurements of NH3 emission from two China 5 and two China 6 light-duty gasoline vehicles (LDGVs) equipped with three-way catalytic converters (TWCs). The results showed that the distance-based emission factors (EFs) were 12.72 ± 2.68 and 3.18 ± 1.37 mg/km for China 5 and China 6 LDGVs, respectively. Upgrades in emission standards were associated with a reduction in tailpipe NH3 emission. In addition, high NH3 EFs were observed during the engine warm-up period in cold-start cases owing to the intensive emissions of incomplete combustion products and suitable catalytic temperature in the TWCs. Notably, based on the instantaneous NH3 emission rate, distinct NH3–emitting events were detected under high/extra high velocity or rapid acceleration. Furthermore, NH3 emission rates correlated well with engine speed, vehicle specific power, and modified combustion efficiency, which were more easily accessible. These strong correlations were applied to reproduce NH3 emissions from China 5/6 LDGVs. The predicted NH3 EFs under different dynamometer and real-world cycles agreed well with existing measurement and prediction results, revealing that the NH3 EFs of LDGVs in urban routes were within 8.55–11.62 mg/km. The results presented here substantially contribute to improving the NH3 emission inventory for LDGVs and predicting on-road NH3 emissions in China.

欧Ⅵ排放测试中使用低浓度标准气的研究

根据试验室中出现的满足欧Ⅵ排放标准的超低排放车辆测量准确性问题,选用了一批超低浓度的标准气,对比研究了超低排放车辆3种低浓度常规污染物在常用标准气和超低浓度标准气下试验的差异。结果表明,国产1×10-6级别浓度标准气能在排放试验室中有效、稳定地使用,且低量程测量能够突显出测试结果的细微差别,可在超低排放车辆的研发过程中提供更准确的数据。

Study about thermal runaway behavior of high specific energy density Li-ion batteries in a low state of charge

Lithium-ion batteries are widely used in electric vehicles and electronics, and their thermal safety receives widespread attention from consumers. In our study, thermal runaway testing was conducted on the thermal stability of commercial lithium-ion batteries, and the internal structure of the battery was analyzed with an in-depth focus on the key factors of the thermal runaway. Through the study of the structure and thermal stability of the cathode, anode, and separator, the results showed that the phase transition reaction of the separator was the key factor affecting the thermal runaway of the battery for the condition of a low state of charge.

Optimal Predictive Control for Path Following of a Full Drive-by-Wire Vehicle at Varying Speeds

The current research of the global chassis control problem for the full drive-by-wire vehicle focuses on the control allocation （CA） of the four-wheel-distributed trac- tion/braking/steering systems. However, the path following performance and the handling stability of the vehicle can be enhanced a step further by automatically adjusting the vehicle speed to the optimal value. The optimal solution for the combined longitudinal and lateral motion control （MC） problem is given. First, a new variable step-size spatial transformation method is proposed and utilized in the prediction model to derive the dynamics of the vehicle with respect to the road, such that the tracking errors can be explicitly obtained over the prediction horizon at varying speeds. Second, a nonlinear model predictive con- trol （NMPC） algorithm is introduced to handle the non- linear coupling between any two directions of the vehicular planar motion and computes the sequence of the optimal motion states for following the desired path. Third, a hierarchical control structure is proposed to separate the motion controller into a NMPC based path planner and a terminal sliding mode control （TSMC） based path fol- lower. As revealed through off-line simulations, the hier- archical methodology brings nearly 1700% improvement in computational efficiency without loss of control per- formance. Finally, the control algorithm is verified through a hardware in-the-loop simulation system. Double-lane- change （DLC） test results show that by using the optimalpredictive controller, the root-mean-square （RMS） values of the lateral deviations and the orientation errors can be reduced by 41% and 30%, respectively, comparing to those by the optimal preview acceleration （OPA） driver model with the non-preview speed-tracking method. Additionally, the average vehicle speed is increased by 0.26 km/h with the peak sideslip angle suppressed to 1.9~. This research proposes a novel motion controller, which provides the full drive-by-wire vehicle with better lane-keeping and colli- sion-avoidance capabilities during autonomous driving.

Variable Parameter Self-Adaptive Control Strategy Based on Driving Condition Identification for Plug-In Hybrid Electric Bus

A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.

Numerical Study on Helical Fiber Fragmentation in Chiral Biological Materials

Chiral microstructures exist widely in natural biological materials such as wood, bone, and climbing tendrils. The helical shape of such microstructures plays an important role in stress transfer between fiber and matrix,and in the mechanical properties of biological materials. In this paper, helical fiber fragmentation behavior is studied numerically using the finite-element method(FEM), and then, the effects of helical shape on fiber deformation and fracture,and the corresponding mechanical mechanisms are investigated. The results demonstrate that, to a large degree, the initial microfibril angle(MFA) determines the elastic deformation and fracture behavior of fibers. For fibers with a large MFA, the interfacial area usually has large values, inducing a relatively low fragment density during fiber fragmentation. This work may be helpful in understanding the relationship between microstructure and mechanical property in biological materials, and in the design and fabrication of bio-inspired advanced functional materials.

Particles Emission from Gasoline Vehicles

Number concentration and size distribution from gasoline ears are investigated at transient modes on the chassis dynamometers, which are measured using electrical low pressure impactor （ELPI） for the ECE15 and EUDC cycles. Results indicate that, during cold start, particle number emission is higher than that under hot start. It is found that the number of particles increases with the vehicle speeds. Furthermore, particles with diameter smaller than 200 nm constitute the predominant part of total emission in the entire cycle. In addition, the tentative information about composition of emitted particles is also discussed.

GB/T 26779-2021《燃料电池电动汽车加氢口》标准分析

With the development of fuel cell electric vehicle industry in China,the 70-MPa hydrogen storage cylinders have been widely applied on vehicles in recent years.The revised standard,GB/T 26779-2021,Hydrogen fuel cell electric vehicle refueling receptacle,was released on March 9,2021 with added stipulations for the 70-MPa hydrogen refuelling receptacle.The main technical contents of GB/T 26779-2021 and its similarities and differences with GB/T 26779-2011 are discussed in this paper.

Dispatching Fuel-cell Hybrid Electric Vehicles Toward Transportation and Energy Systems Integration

With the increasing integration of traditional elec-tric vehicles(EVs),the ensuing congestion and overloading issues have threatened the reliability of power grid operations.Hydrogen has been advocated as a promising energy carrier to achieve low-carbon transportation and energy(trans-energy)systems,which can support the popularization of fuel-cell hybrid EVs(FCHEVs)while enhancing the flexibility of power grids.In this paper,we propose an optimal scheduling framework for trans-energy systems that evaluates the merits of the hydrogen supply chain from water electrolysis,compressed storage and transportation to FCHEV utilization.A detailed FCHEV model is established,and mileage is modeled as a function of the stored electricity and hydrogen mass.A stochastic programming-based scheduling model is formulated,which minimizes the total cost of unit commitment and the hydrogen supply chain.The Dijkstra algorithm is adopted to search the shortest path for hydrogen transportation.Case studies demonstrate that FCHEVs can reduce the operational costs of tran-energy systems and facilitate the accommodation of renewable energy when compared to traditional EVs.Index Terms-Fuel-cell hybrid electric vehicle,hydrogen,mileage model,shortest path search,trans-energy systems.

Three-Dimensional Conformal Dose Planning for Prostate Brachytherapy

For local radiotherapy, a three-dimensional(3D)conformal localized dose planning protocol has been established in this paper to develop a precise and reasonable dose plan. A precalculated 3D dose map for a single source is obtained using the Monte Carlo method, and the spatial dose maps are combined linearly to acquire the dose distribution. The dose distribution is visualized through the real-time display of the isodose line and isodose surface combined with the reconstructed 3D organ groups. By observing 3D dose coverage to the target volume and surrounding tissues, dose planning could be initiated with greater accuracy and precision to avoid dose dead zones and excessively high-dose levels, thus achieving the 3D conformal dose planning objective. Further research into the impact that blockages have on a needle trajectory can be conducted to optimize the insertion accuracy. A treatment planning system was developed to formulate and implement the 3D local treatment plan before the surgery,during the surgery, and after the surgery. Several experiments pertaining to both single-seed and multiple-seed dose distributions were conducted to verify the accuracy of the single-seed dose calculation module and 3D superposition dose calculation in the treatment planning system.

Theory of Vehicle's Durability Correlation Test

The theory of vehicle's correlation tests was discussed and the correlation test mathematical model was created. According to the damage theory, the correlation equation was brought up. The method to solove it was given. The text gives the theory basis of vehicle's correlation tests. The results can be used to give the vehicle's test designation and to make the test to fit the actual environments. Besides that, the methods give acceleration and strengthen effects.

Variability of fuel consumption and CO_(2) emissions of a gasoline passenger car under multiple in-laboratory and on-road testing conditions

An increasing divergence regarding fuel consumption(and/or CO_(2)emissions) between realworld and type-approval values for light-duty gasoline vehicles(LDGVs) has posed severe challenges to mitigating greenhouse gases(GHGs) and achieving carbon emissions peak and neutrality. To address this divergence issue, laboratory test cycles with more real-featured and transient traffic patterns have been developed recently, for example, the China Lightduty Vehicle Test Cycle for Passenger cars(CLTC-P). We collected fuel consumption and CO_(2)emissions data of a LDGV under various conditions based on laboratory chassis dynamometer and on-road tests. Laboratory results showed that both standard test cycles and setting methods of road load affected fuel consumption slightly, with variations of less than 4%. Compared to the type-approval value, laboratory and on-road fuel consumption of the tested LDGV over the CLTC-P increased by 9% and 34% under the reference condition(i.e., air conditioning off, automatic stop and start(STT) on and two passengers). On-road measurement results indicated that fuel consumption under the low-speed phase of the CLTC-P increased by 12% due to the STT off, although only a 4% increase on average over the entire cycle. More fuel consumption increases(52%) were attributed to air conditioning usage and full passenger capacity. Strong correlations(R2> 0.9) between relative fuel consumption and average speed were also identified. Under traffic congestion(average speed below 25 km/hr), fuel consumption was highly sensitive to changes in vehicle speed. Thus,we suggest that real-world driving conditions cannot be ignored when evaluating the fuel economy and GHGs reduction of LDGVs.

Review on recent progress in on-line monitoring technology for atmospheric pollution source emissions in China

Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,such as NH3and NOx,are the most harmful to human health.China has released various regulations and standards to address pollution from mobile and stationary sources.Thus,it is urgent to develop online monitoring technology for atmospheric pollution source emissions.This study provides an overview of the main progress in mobile and stationary source monitoring technology in China and describes the comprehensive application of some typical instruments in vital areas in recent years.These instruments have been applied to monitor emissions from motor vehicles,ships,airports,the chemical industry,and electric power generation.Not only has the level of atmospheric environment monitoring technology and equipment been improving,but relevant regulations and standards have also been constantly updated.Meanwhile,the developed instruments can provide scientific assistance for the successful implementation of regulations.According to the potential problem areas in atmospheric pollution in China,some research hotspots and future trends of atmospheric online monitoring technology are summarized.Furthermore,more advanced atmospheric online monitoring technology will contribute to a comprehensive understanding of atmospheric pollution and improve environmental monitoring capacity.

Modeling and optimal energy management of a power split hybrid electric vehicle

With the combination modes of engine and two electric machines,the power split device allows higher efficiency of the engine.The operation and of a power split HEV are analyzed,and the system dynamic model HEV is established event-driven for HEV forward system simulation dynamics controller design.Considering the mode,the fact the mode that the operation modes of is the are and the the is continuous theory.time-driven this for each structure selection of the controller built and the described finite with hybrid automaton control In control structure,process is depicted by the state mode machine(FSM).The multi-mode switch controller is designed to realize power distribution.Furthermore,vehicle operations programming are optimized,and finite the prediction nonlinear model horizon.predictive control(NMPC)strategy is applied by that implementing the dynamic(DP)and in the Comparative simulation The results optimal demonstrate strategy hybrid in control structure is effective feasible for HEV energy management design.NMPC is superior improving fuel economy.

Development and experimental validation of a novel hybrid powertrain with dual planetary gear sets for transit bus applications

Given that energy conservation and environmental protection are two important goals for the automotive industry, the application of a hybrid electric powertrain can improve vehicle energy efficiency while decreasing fuel consumption and engine emissions. Planetary gear-based power-split hybrid powertrains have become widely used in passenger vehicles, but remain rarely employed on transit buses. This study proposes a novel hybrid powertrain based on two planetary gear sets(CHS) and presents its operating principles along with development of a control strategy for the powertrain. The CHS hybrid powertrain operates in electric mode when the driving power demand is low, and changes to a hybrid electric mode according to the power-split principle of the planetary gear set. To validate the feasibility of the designed CHS hybrid powertrain, a prototype transit bus equipped with the designed hybrid powertrain system was built, and the operating characteristics of the system were analyzed through a performance test conducted on a chassis dynamometer. Compared with a conventional powertrain, the CHS hybrid powertrain can reduce fuel consumption by 39%. Thus, the CHS hybrid powertrain is a good solution for heavy-duty applications such as hybrid transit buses because of its simple structure and excellent fuel efficiency.

Application of complete ensemble intrinsic time-scale decomposition and least-square SVM optimized using hybrid DE and PSO to fault diagnosis of diesel engines

针对固有时间尺度分解算法的模态混叠问题和最小二乘支持向量机的参数优化问题,本文提出了一种新的基于完备集合固有时间尺度分解和混合差分进化和粒子群算法优化最小二乘支持向量机的柴油机故障诊断方法。该方法主要包括以下几个步骤:首先,为解决固有时间尺度分解算法的模态混叠问题,提出了一种完备集合固有时间尺度分解算法。随后,利用完备集合固有时间尺度分解算法将非平稳的柴油机振动信号分解为一系列平稳的旋转分量和残差信号。然后,提取了前几阶旋转分量的三类典型的时频特征,包括奇异值、旋转分量能量和能量熵、AR模型参数,作为故障特征。最后,提出了混合差分进化和粒子群算法对最小二乘支持向量机的参数进行优化的方法,并通过将故障特征输入训练好的最小二乘支持向量机模型实现故障诊断。仿真和实验结果表明提出的故障诊断方法可以克服固有时间尺度分解的模态混叠问题,而且能够准确的识别柴油机故障。