This paper presents the development of SmartDrive package to achieve the application of energy-efficient driving strategy. The results are from collaboration between Ricardo Rail and the Birmingham Centre for Railway Research and Education (BCRRE). Advanced tram and train trajectory optimization techniques developed by BCRRE as part of the UKTRAM More Energy Efficiency Tram project have been now incorporated in Ricardo's SmartDrive product offering. The train trajectory optimization method, associated driver training and awareness package (SmartDrive) has been developed for use on tram, metro, and some heavy rail systems. A simulator was designed that can simulate the movement of railway vehicles and calculate the detailed power system energy consumption with different train trajectories when implemented on a typical AC or DC powered route. The energy evaluation results from the simulator will provide several potential energy-saving solutions for the existing route. An enhanced Brute Force algorithm was developed to achieve the optimization quickly and efficiently. Analysis of the results showed that by implementing an optimal speed trajectory, the energy usage in the network can be significantly reduced. A driver practical training system and the optimized lineside driving control signage, based on the optimized trajectory were developed for testing. This system instructed drivers to maximize coasting in segregated sections of the network and to match optimal speed limits in busier street sections. The field trials and real daily operations in the Edinburgh Tram Line, U.K., have shown that energy savings of 10%-20% are achievable.

According to the specific requirements of railway engineering, a techno-economic comparison for onboard hydrogen storage technologies is conducted to discuss their feasibility and potentials for hydrogen-powered hybrid trains. Physical storage methods, including compressed hydrogen (CH₂), liquid hydrogen (LH₂), and cryo-compressed hydrogen (CcH₂), and material-based (chemical) storage methods, such as ammonia, liquid organic hydrogen carriages (LOHCs), and metal hydrides, are carefully discussed in terms of their operational conditions, energy capacity, and economic costs. CH₂ technology is the most mature now but its storage density cannot reach the final target, which is the same problem for intermetallic compounds. In contrast, LH₂, CcH₂, and complex hydrides are attractive for their high storage density. Nevertheless, the harsh working conditions of complex hydrides hinder their vehicular application. Ammonia has advantages in energy capacity, utilisation efficiency and cost, especially being directly utilised by fuel cells. LOHCs are now considered as a potential candidate for hydrogen transport. Simplifying the dehydrogenation process is the important prerequisite for its vehicular employment. Recently, increasing novel hydrogen-powered trains based on different hydrogen storage routes are being tested and optimised across the world. It can be forecasted that hydrogen energy will be a significant booster to railway decarbonisation.

The simulation of railway systems plays a key role in designing the traction power supply network, managing the train operation, and making changes to timetables. Various simulation technologies have been developed to study the railway traction power network and train operation independently. However, the interactions between the load performance, train operation, and fault conditions are not fully understood. This paper proposes a mathematical modeling method to simulate the railway traction power network with a consideration of a multi-train operation, driving controls, under-voltage traction, and substation fault modes. The network voltage, power load demands, and energy consumption according to the existing operation are studied. The hotspots of the power supply network are identified based on an evaluation of the train operation and power demand. The impact of traction power substation (TPSS) outage and a short circuit on the power supply network have been simulated and analyzed. The simulation results have been analyzed and compared with those of a normal operation. A case study based on a practical metro line in Singapore is developed to illustrate the power network evaluation performance.

Train‐centric communications‐based train control (TcCBTC) system is a new solution for urban transit signalling. Compared to traditional train control systems, the on‐board equipment is becoming more powerful and more complex. Due to its safety‐critical nature, specialised technologies must be adopted to guarantee the safety of the system. To address the safety verification difficulty of the control logic for the new system, this study presents an innovative topology‐based method for guaranteeing the train control safety. First, a railway network is described as a metric space, and then, topological spaces are introduced to express the movement authority and train trajectory. On the basis of the topological description, the safety rules are checked by performing a series computation of topology theorems. Finally, a case study has been carried out on a real metro line in China. The result shows that the proposed method strictly meets the safety verification and achieves excellent performance.

A dual mode traction power supply system (TPSS), as a high-efficiency transportation approach, is composed of a mainline railway (AC traction power supply system) and an urban railway (DC traction power supply system). However, due to the neutral sections, the power from the two systems has been isolated, resulting in a low utilization rate of regenerative braking energy (RBE). The power flow from the two systems can not be managed cooperatively, causing high electricity bills. Therefore, this paper proposes a dual mode based energy router (DMER), which provides a path for energy interaction between two systems through multi-terminal converters. The proposed DMER integrates a hybrid energy storage system (HESS) and an energy feedback system (EFS) to recycle RBE. Moreover, a hierarchical control strategy is presented. The upper control layer is an optimized operation model, which takes the state of charge (SoC), energy conservation, and the other parameters as constraints to utilize more RBE and achieve the minimum daily operation cost of substations. The lower control layer identifies the control strategy for multiple converters to ensure the stable operation and dynamic response of DMER. Finally, the effectiveness of the topology and control strategy is verified using field load data and experiments.

This paper presents a fuzzy adaptive protective control method for autonomous high-speed trains (HSTs) automatic operation using a new outstretched error feedback design approach. In order to stabilizing the error dynamics with respect to target position and speed profiles of controlled HSTs, nonlinear transformation in prescribed performance control methodology is used to convert running states subject to protective (constrained) information, imposed by automatic train protection (ATP) subsystem, to new coordinates in unconstrained form. By blending a new outstretched error feedback and fuzzy approximation, it is guaranteed above-mentioned errors are kept within regions characterized by error boundary (or prescribed performance) functions and control parameters simultaneously, which can be adjusted to arbitrarily small even without error decreasing boundary functions. Fuzzy approximation is used in compensating unknown running resistances. It is rigorously proved that the resulting closed-loop system is stable in sense of Lyapunov stability in the presence of unknown resistance, containing basis and aerodynamic resistances with uncertain parameters and piecewise continuously slope resistance over varying gradient profile. The proposed control is demonstrated to be effective by comparative simulations of train G1 running on Beijing-Shanghai railway line.