Liangliang Chen

Charging load prediction of electric vehicles (EVs) is an important prerequisite for studying the interaction between electric vehicles and power grid. Aiming at the influence of traffic road network information on the driving rule of EVs, a spatial-temporal distribution prediction method of charging load for EVs based on dynamic traffic information is presented. In this methodology, given the characteristic of multiple intersections in the urban road network, a dynamic road network model with the impedance of the road section and the impedance of the node are established firstly. The corresponding interactive model of transportation network-distribution network is determined according to the scale of road network. And then, the origin destination (OD) matrix analysis method and the real-time Dijkstra dynamic path search algorithm are introduced to assign start-stop nodes and plan driving paths for EVs and simulate their dynamic driving process and charging behavior. At last, the EV path planning experiment and the charging load prediction experiment in typical regions are designed to verify the effectiveness and feasibility of the proposed strategy.

A modified one-dimensional testing apparatus that incorporates a bender–extender element system and tactile pressure sensors was developed for the monitoring of particle crushing. The apparatus was tested using five types of glass beads with different particle sizes. The compressional shear wave velocities and their ratio were evaluated with respect to the porosity to establish the microstructural evolution of the granular material. The results showed that the bender–extender element system functioned excellently under high-pressure one-dimensional compression, with the shear wave velocity ratio increasing with increasing loading stress up to 7 MPa and thereafter decreasing. The loading stress of 7 MPa was thus considered the breakage stress of the glass beads, as also reflected by a sharp increase in strain. The glass beads subsequently entered Stage 2 of the crushing process, characterized by significant crushing. Arching of the particle assembly was also clearly observed, and this was enhanced by an increase in the roughness of the side plates of the container. An empirical equation for evaluating the arching was derived. The microstructural evolution and macro behavior of the glass beads under the constrained boundary condition and high compression pressure were found to be analogous to those of the crushing of high-porosity sandstone.