Charge state of battery is one of the important parameters of battery. Accurate estimation of SOC can improve battery safety, prolong battery life and improve battery utilization efficiency. Straightforward valuation of battery SOC is very essential for retired electric vehicle batteries. The traditional SOC estimation method based on extended Kalman filter (EKF) is excessively dependent on the accurate battery model, and requires that the system noise must be subject to Gaussian white noise, and the SOC prediction error is large. To address the mentioned above existing problems, a method based on Recurrent Neural Networks (RNN) to correct the SOC error of Extended Kalman Filter is proposed to realize the accurate estimation of SOC. By comparing the experimental results, it can be obtained that its algorithm can accurate to predict SOC, and the error is within 1.3 %. and has good convergence and robustness, which has high practical application value.

This paper proposes an adaptive fault-tolerant control scheme for nonaffine nonlinear systems. A model approximation method which is a solution that bridges the gap between affine and nonaffine control systems is developed firstly. A joint estimation approach is based on unscented Kalman filter, in which both failure parameters and states are simultaneously estimated by means of the argument state vector composed of the unknown faults and states. Then, stability analysis is given for the closed-loop system. Finally, the proposed approach is verified using a three-degree-of-freedom simulation of a typical fighter aircraft and the significantly improved system response demonstrates the practical potential of the theoretic results obtained.

The increasing integration of renewable energy is challenging the secure operation of the power system. System flexibility or the capability to address the significant power fluctuations from renewable energy is becoming more and more relevant. Self-energy storage-based multiterminal back-to-back VSC-HVDC (SES-VSC-MTDC) technology is first proposed, and it can realize the power regulation on both temporal and spatial dimensions, which helps improve the power supply reliability and the capacity to accommodate renewable energy of the interconnected distribution networks. Then, to address the coordination control problem of the energy storage and back-to-back VSC-HVDC, a comprehensive control strategy of SES-VSC-MTDC is proposed based on the optimal power flow preprocessing and state of charge interval division. Then, the power regulation model and the energy-power regulation timing model of SES-VSC-MTDC are established for different control strategies. Then, we use the primal-dual interior-point method to solve the developed optimal operation model of flexible interconnected distribution network. Finally, a 33-bus system with four interconnected feeders is used to test the effectiveness of the SES-VSC-MTDC technology and its operation control strategy.