The volume of the metallic lithium anode in allsolid-state Li metal batteries increases significantly due to the lithium dendrite formation during the battery cycling, and the rough surface of lithium metal also reduces Li-ion transport in Li/electrolyte interface. In this work, we developed a solid polymer composite by adding the lowcost Si 3 N 4 particles to protect the lithium anode in allsolid-state batteries. The Fourier transform infrared spectroscopy (FTIR) data show that the surface of 10 wt % Si 3 N 4 particles interacts with the polyethylene oxide (PEO) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt; the interaction restricts the anion mobility and improves the ionic conductivity (1 9 10 -4 SÁcm -1 ) and lithium-ion transference number (0.28) of the composite electrolyte. The lithium metal anode is well protected by the composite electrolyte in all-solid-state cells, including symmetric and Li/LiFePO 4 cells. The lithium dendrite growth suppression by this composite electrolyte indicates the possible application of these low-cost composite electrolytes for lithium metal protection.
The effects of various sintering parameters (temperature, time and nitrogen pressure) on the density, nitrogen content and the mechanical properties of high nitrogen nickel free austenitic stainless steel (0Cr-17Mn-11Mo-3N) prepared by powder injection moulding were investigated, and the influence of solution annealing on the microstructure and mechanical properties was also discussed. The results show that the optimal sintering conditions are as follows: sintering temperature 1300uC, sintering time 2 h and nitrogen pressure 0?1 MPa, under which a favourable combination of the relative density of 99?1% and the nitrogen content of 0?78 wt-% can be obtained. After solution annealing at 1150uC for 90 min, the yield strength and ultimate tensile strength can reach 580 and 885 MPa respectively, which are about 2?9 and 1?7 times greater than those of 316L Metal Injection Molding (MIM) stainless steel. Before solution annealing, the sintered specimens mainly consist of c-austenite, a-ferrite and network of Cr 2 N phase, while after solution annealing, they reveals a fully austenitic structure without any intergranular nitrides.
Aiming at solving problem of vehicle state estimation, an adaptive fading unscented Kalman filter(AFUKF) algorithm was proposed. Based on this purpose, a 7-DOF nonlinear vehicle model with the Pacejka nonlinear tire model was established firstly. Then, the vehicle state estimator based on Kalman filter was designed to solve the problem of vehicle state estimation. The simulation verification shows the effectiveness and reliability of the designed estimator for vehicle state estimation. Compared with other traditional methods, the calculation accuracy is higher for the AFUKF algorithm to solve the problem of vehicle state estimation. The study can help drivers easily identify key state estimation in safe driving area.
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