In order to absorb the regenerative braking energy of trains, supercapacitor energy storage systems (ESS) are widely used in subways. Although stationary ESS are widely used, because of the influence of no-load voltage, and so on, a stationary ESS cannot absorb all the regenerative braking energy in some special cases, and the brake resistor is still activated, which leading to the wasting of energy. In order to completely replace the on-board brake resistor, this paper configures a certain on-board supercapacitor, and based on a DC-side series supercapacitor topology, proposes a hierarchical optimization energy management strategy (EMS). The EMS is divided into three layers: Firstly, the strategy can increase the inverter-side voltage in a short time without changing the traction network voltage, and improve the train braking characteristic curve by utilizing the short-time overvoltage capability of the inverter and the motor; Secondly, by coordinated control with a stationary supercapacitor, the residual regenerative braking energy can be absorbed even in special cases; Finally, based on loss calculation and current prediction, this strategy can effectively reduce the system loss by adjusting the DC voltage on the inverter-side. The proposed control strategy is validated through simulation and RT-LAB experiment, and the experimental results agree well with the theory.

This paper proposes a sensorless control strategy for permanent magnet synchronous motors (PMSMs) based on a sliding mode observer (SMO), and high-speed PMSM sensorless velocity control is realized. To solve the serious chattering and phase lag problems of conventional SMOs, the continuous function is used as the control function, and the low-pass filter is improved into a back electromotive force (EMF) observer with an adaptive structure. In addition, the phase-locked loop is combined to perform the SMO-based sensorless control. The simulations and experiments prove the effectiveness of the proposed strategy.

There are three major challenges to the broad implementation of energy storage systems (ESSs) in urban rail transit: maximizing the absorption of regenerative braking power, enabling online global optimal control, and ensuring algorithm portability. To address these problems, a coordinated control framework between onboard and wayside ESSs is proposed in this study, and the related control strategy is obtained by transforming the global optimization problem into a combination of rule-based and local optimization problems. The design process of the strategy is divided into three parts: offline optimization, rule extraction, and local optimization. First, a genetic algorithm is used to optimize the charge/discharge threshold curves under typical operational conditions. Then, the rules of offline optimization results are obtained from an expert system, and the nonlinear rules are mined with local optimization methods. Finally, a coordinated strategy is presented based on the outcomes of the three parts. A power hardware-in-the-loop (PHIL) experimental platform based on RTLAB is built, and the above coordination strategy is verified based on data for the Beijing Metro Batong Line. The experimental results show that the strategy can effectively improve the energy-saving rate and reduce the regeneration failure rate substantially, with the effect being close to the offline global optimal solution. The algorithm proposed in this paper achieves near global optimal energy-saving optimization results with lower computational costs, and has strong portability, providing a good solution for the large-scale application of onboard and wayside energy storage coordination control.

A prerequisite for regenerative braking energy recovery in urban rail transit is to clarify how power flows between sources and loads in the system. Different from power flow calculation, which focuses on specific voltage and current values of each branch, power flow tracing emphasizes the contributions of sources to a specific load (upstream tracing) and the corresponding dual problem (downstream tracing). Considering the time-varying characteristics of urban rail transit, a dynamic current tracing approach based on circuit theory and the state variable method is proposed to describe the current distribution relationship between sources and loads. Thereafter, by applying fundamental circuit laws, the disaggregation result of current is straightforwardly extended to power tracing, and thus the power share that each source provides to each load (and the dual problem) can be determined. A rigorous mathematical proof is given for the derivation of tracing coefficients. Finally, a case study is implemented to verify the applicability of the proposed method. Through power flow tracing, the quantified and intuitive description of the current and power distribution relationship between sources and loads is demonstrated, which can provide a theoretical basis for future research on the optimal design and coordinated control of various braking energy recovery devices.

Sensorless induction motor control has been widely applied to the rail transit field. However, achieving a safe stop of a train using electric braking without applying air braking has been an urgent problem to be solved. The current research only considers the stability of the speed identification in the low‐speed region and does not consider the impact of inaccurate parameters on the stability, which cannot ensure the stable braking and parking of the train under all working conditions. To address this problem, the coupling relationship between the motor speed and the stator resistance is used and an adaptive rate of them is designed based on the Lyapunov stability design law. In addition, aiming to reduce the torque ripple, a torque ripple elimination link is designed to cancel the torque ripple caused by the small‐signal injection. Experiments show that the proposed parallel identification strategy of speed, stator resistance, and rotor resistance can ensure the system operation stability in the low‐ and zero‐speed regions without increasing the torque ripple.