This article presents a review of cutting-edge technologies poised to shape the future of railway transportation systems, focusing on enhancing their intelligence, safety, and environmental sustainability. It illustrates key aspects of the energy-transport-information/communication system nexus as a framework for future railway systems development. Initially, we provide a review of the existing challenges within the realm of railway transportation. Subsequently, we delve into the realm of emerging propulsion technologies, which are pivotal for ensuring the sustainability of transportation. These include innovative solutions such as alternative fuel-based systems, hydrogen fuel cells, and energy storage technologies geared towards harnessing kinetic energy and facilitating power transfer. In the following section, we turn our attention to emerging information and telecommunication systems, including Long-Term Evolution (LTE) and fifth generation New Radio (5G NR) networks tailored for railway applications. Additionally, we delve into the integral role played by the Industrial Internet of Things (Industrial IoT) in this evolving landscape. Concluding our analysis, we examine the integration of information and communication technologies and remote sensor networks within the context of Industry 4.0. This leveraging of information pertaining to transportation infrastructure promises to bolster energy efficiency, safety, and resilience in the transportation ecosystem. Furthermore, we examine the significance of the smart grid in the realm of railway transport, along with the indispensable resources required to bring forth the vision of energy-smart railways.

This paper presents the novel design of a constant-current/constant-voltage charging control strategy for a battery cell. The proposed control system represents an extension of the conventional constant-current/constant-voltage charging based on the so-called cascade control system arrangement with the adaptation of the battery charging current based on the open-circuit voltage parameter estimation. The proposed control strategy features two feedback controllers of the proportional-integral type responsible for: (i) controlling the battery open-circuit voltage towards its fully charged state, and (ii) simultaneously limiting the battery terminal voltage to avoid the battery terminal voltage constraint violation. The open-circuit voltage on-line estimation is implemented by using the system reference adaptive model approach to estimate the linear time-invariant battery equivalent circuit model parameters, whose asymptotic convergence is guaranteed according to Lyapunov stability theory. The proposed concept of the battery charging control is verified by means of simulations using the experimentally obtained model of a lithium iron phosphate battery cell, and it is also compared to other charging methods with respect to charging speed-up potential compared to conventional charging. The proposed method, which can be easily extended to conventional chargers, results in 23.9% faster charging compared to conventional charging, thus representing an inexpensive and straightforward upgrade to conventional battery charging systems.

Hybrid electric propulsion, using batteries for energy storage, is making significant inroads into railway transportation because of its potential for notable fuel savings and the related reductions in greenhouse gases emissions of hybrid railway traction over non-electrified railway lines. Due to the inherent complexity of hybridized powertrains, combining different power conversions and energy storage capabilities, the corresponding operation of their energy management needs to be precisely optimized in order to achieve the minimum possible fuel consumption. Having this in mind, this paper proposes a real-time energy management control strategy for a diesel–electric hybrid locomotive based on the optimization results obtained by means of a dynamic programming optimization algorithm aimed at fuel consumption minimization while honoring the battery state-of-charge constraints and powertrain physical constraints. The final optimization result, expressed in terms of the optimal battery state-of-charge reference (target), is used as an additional input into the state-of-charge controller within the real-time energy management system. The subsequent simulation analysis shows clear fuel economy improvement with 22.9% of fuel savings obtained for the locomotive featuring a hybrid powertrain equipped with batteries over the conventional one.

The paper presents a hypothetical conversion of a conventional cable skidder powertrain to its hybrid version. Simulations of skidder operation were made for two existing forest paths, based on the technical characteristics of the engine, transmission system and the characteristics of the winch. Fuel and time consumption were calculated per working cycle considering the operating conditions (slope, load mass). The model was then converted to a hybrid version by adding a battery energy storage system in parallel with the electrical power generator and by employing an energy management control strategy. The dimensions of the battery and the power generator were chosen based on the characteristics of the existing winch with the aim of completely taking over its operation. The management strategy was selected using the specific fuel consumption map. All simulations were repeated for the hybrid drive under the same operating conditions. The results show that fuel savings of around 13% can be achieved with the selected hybrid drive and steering strategy.

This paper presents the results of modeling, control system design and simulation verification of a hybrid-electric drive topology suitable for power flow control within unmanned aerial vehicles (UAVs). The hybrid power system is based on the internal combustion engine (ICE) driving a brushless DC (BLDC) generator supplying the common DC bus used for power distribution within the aircraft. The overall control system features proportional-integral-derivative (PID) feedback control of the ICE rotational speed using a Luenberger estimator for engine-generator set rotational speed estimation. The BLDC generator active rectifier voltage and current are controlled by proportional-integral (PI) feedback controllers, augmented by estimator-based feed-forward load compensators. The overall control system design has been based on damping optimum criterion, which yields straightforward analytical expressions for controller and estimator parameters. The robustness to key process parameters variations is investigated by means of root-locus methodology, and the effectiveness of the proposed hybrid power unit control system is verified by means of comprehensive computer simulations.