Accurate prediction of the remaining useful life (RUL) is a key function for ensuring the safety and stability of lithium-ion batteries. To solve the capacity regeneration and model adaptability under different working conditions, a hybrid RUL prediction model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a bi-directional gated recurrent unit (BiGRU) is proposed. CEEMDAN is used to divide the capacity into intrinsic mode functions (IMFs) to reduce the impact of capacity regeneration. In addition, an improved grey wolf optimizer (IGOW) is proposed to maintain the reliability of the BiGRU network. The diversity of the initial population in the GWO algorithm was improved using chaotic tent mapping. An improved control factor and dynamic population weight are adopted to accelerate the convergence speed of the algorithm. Finally, capacity and RUL prediction experiments are conducted to verify the battery prediction performance under different training data and working conditions. The results indicate that the proposed method can achieve an MAE of less than 4% with only 30% of the training set, which is verified using the CALCE and NASA battery data.

The field of sensorless control of permanent magnet synchronous motor (PMSM) systems has been the subject of extensive research. The accuracy of sensorless controllers depends on the precise estimation of PMSM state quantities, including rotational speed and rotor position. In order to enhance state estimation accuracy, this paper proposes a moving horizon estimator that can be utilized in the sensorless control system of PMSM. Considering the parameter variations observed in PMSM, a nonlinear mathematical model of PMSM is established. A model reference adaptive system (MRAS) is employed to identify parameters such as resistance, inductance, and magnetic chain in real time. This approach can mitigate the impact of parameter fluctuations. Moving horizon estimation (MHE) is an estimation method based on optimization that can directly handle nonlinear system models. In order to eliminate the influence of external interference and improve the robustness of state estimation, a method based on MHE has been designed for PMSM, and a sensorless observer has been established. Considering the traditional MHE with large computation and high memory occupation, the calculation of MHE is optimized by utilizing a Hessian matrix and gradient vector. The speed and position of the PMSM are estimated within constraints during a single-step iteration. The results of the simulation demonstrate that in comparison to the traditional control structure, the estimation error of rotational speed and rotor position can be reduced by utilizing the proposed method. A more accurate estimation can be achieved with good adaptability and computational speed, which can enhance the robustness of the control system of PMSM.

The safety risk assessment system for urban rail transit operations has been studied to provide support and guidance for rail transit operations. Firstly, a risk assessment index system for rail transit operations is established from four levels: station train operation, station passenger capacity, station environment, and station equipment services, providing support for the safe and reliable operation assessment of rail transit. Then, a risk assessment model for rail transit operation safety is proposed, and an improved AHP method is used to determine the weight of the indicators. Then, evaluation scores of indicators at all levels are obtained based on the cloud model assessment method, in order to evaluate the risk level of rail transit operation, providing a judgment basis for rail transit safety operation.

Based on the similar characteristics of installation about the penetrometer of seismic piezocone penetration tests(SCPTu) and the single pile, a theoretical relationship between ultimate bearing capacity of single pile, time-effect of shaft bearing capacity of single pile, excess pore water pressure around the pile during pile driven and the data measured from SCPTu is developed according to the cavity expanded theory, the Terzaghi one-dimensional consolidation theory and effective stress theory. The result of field test in KunShan and the calculated result which used the theoretical relationship mentioned above are compared. The results indicate that the analytical solutions agree well with the in-situ tests, which show that the applications of seismic piezocone penetration tests have wide range in the design of pile foundation.