One of the key strategies to reduce fuel consumption and emissions is given by engine downsizing, together with turbocharging. Under this aspect, the possibility to couple an electric drive to the turbocharger to recover the residual energy of the exhaust gases is becoming more and more attractive. However, additional energy coming from an electric turbo compound (ETC) application has to be managed by the vehicle powertrain through a proper energy management strategy. This study shows the numerical results of a research programme under way focused on the comparison of the benefits resulting from the application of two ETC configurations to a medium size vehicle equipped with a small four cylinders turbocharged diesel engine (1561 cm³). Starting from the experimental maps of the turbine and compressor, the complete engine model was created using a commercial one-dimension code. The numerical activity then moved to the whole vehicle modelling. Engine results have been used to properly define a powertrain architecture and energy management strategy in order to maximise the benefits coming from the single-ETC or the dual-ETC solution. Finally, vehicle performance and energy flows have been analysed in different real driving conditions and compared to the original vehicle without ETC.

This is a concept research study and describes a mechanism in which an electric power generation process is integrated within the body of the internal combustion engine structure. It includes a core made of magnetic material which is excited by a coil. This magnetic core is a part of the engine block structure itself. Concurrently, the engine piston is modified by having a disc made of magnetic material forming part of the piston structure itself. Electric power is generated by the reciprocating motion of the piston, using the principle of variation of the coil inductance with reluctance, caused by the reciprocating motion. The proposed system completely eliminates the need to have a pulley and belt mechanism. Hence there are no additional moving parts in the system, and the already existing motion of the piston is utilised in the process. In addition, multiple cylinders in the vehicle allow duplicating the generator mechanism in each of the cylinders, and thus providing redundancy and enhanced overall system reliability. The proposed system can actually be used in both generation and propulsion modes, and also allowing regenerative braking, if desired, and hence opening up possibilities for mild hybrid type of vehicular operation.

This study investigates the ability of temperature sensors installed in the traction core of trains to early detect incipient faults. For instance, the breaking of a bearing is known to be critical as it may cause an increase of the temperature in the motor compartment, that in turn may eventually lead to a winding fault in the induction motor. The technique proposed in this contribution is characterised by extreme generality, since most frequent incipient faults lead to temperature increase that, if properly analysed, can be a tool for preventive maintenance. In particular, the measured data, provided by the main Italian railway company, are processed by two different methodologies which are characterised by positive, yet different, performances. The results show that preventive maintenance with the proposed approach is feasible.

This study presents an innovative electronic–magnetic geared motor technology for electric vehicles (EVs). The motor has been designed and simulated. The electronic–magnetic gearing (EMG) connects parallel, series or hybrid connections of stator windings into gears to accommodate the different speed and torque demands in the drive cycle. The objective of the EMG is to increase the speed and torque range of the motor and reduce current draw from the batteries. A 1.5 kW prototype EMG motor was built and tested on a test rig at Electronica Products Ltd. A comparison simulation of an EMG motor compared with a traditional permanent magnet synchronous motor was also carried out. The result proves that the theory of EMG is sound and it has great potential for energy efficiency in EVs, especially for the powertrain units.

A single-stage-based integrated power electronic converter has been proposed for plug-in electric vehicles (PEVs). The proposed converter achieves all modes of vehicle operation, i.e. plug-in charging, propulsion and regenerative braking modes with wide voltage conversion ratio (M) [M < 1 as well as M > 1] in each mode. Therefore, a wide variation of battery voltage can be charged from the universal input voltage (90–260 V) and allowing more flexible control for capturing regenerative braking energy and dc-link voltage. The proposed converter has least components compared to those existing converters which have stepping up and stepping down capability in all modes. Moreover, a single switch operates in pulse width modulation in each mode of converter operation hence control system design becomes simpler and easy to implement. To correctly select the power stage switches, a loss analysis of the proposed converter has been investigated in ac/dc and dc/dc stages. Both simulation and experimental results are presented to validate the operation of the converter.

Diesel is the most common energy source used by many railway vehicles globally but it also has an impact on the environment due to carbon emissions from the diesel engine. Railway electrification is an effective way to reduce emissions but fails to be a very cost effective solution particularly for routes where passenger traffic is low. This study has undertaken a propulsion system concept design based on a vehicle similar to the British class 150 diesel-powered vehicle. A return journey was simulated over the British regional route Birmingham Moor Street to Stratford-upon-Avon to set a benchmark for the development of hydrogen-powered and hydrogen-hybrid trains. A fuel cell power plant and hydrogen compressed at 350 bars were used as part of the concept design. It was found that all the components essential for the train propulsion system can be installed within the space available on original diesel-powered class 150 train. The installation of equipment does not compromise passenger capacity and weighs similar to original class 150. Energy consumption was reduced by 44% on the hydrogen-powered train and by 60% on the hydrogen-hybrid train. Carbon-dioxide emissions were reduced by 59% using the hydrogen-powered train and by 77% using the hydrogen-hybrid train.

This study focuses on the topic of energy efficiency for railway application. A case study extrapolated from a real system was approached. An entire railway infrastructure, constituted by an alternating current (AC) primary grid, a direct current (DC) railway system and some AC/DC railway electrical substations (ESSs), was observed. The considered system was represented to study the operation of the railway infrastructure in terms of energy. A method, based on an AC/DC power flow approach, was formulated to calculate the efficiency in the use of electrical energy, during the motion of a fleet of trains. The method reports the solution vector (i.e. the AC and DC voltages and currents) as a function of the scheduling of the railway service. The results of the numerical simulations focused on the energy amounts at the ESS. The discussion gives evidence to the impact of alternative operating solutions in terms of energy efficiency strategies.

Business models for battery swapping stations (BSS) have been emerging as influenced by the increased attention to electric vehicles (EVs) and the deregulation of the electricity market. BSS may also provide support mechanisms for a sustainable EV ecosystem, but swapping stations are still at an early stage and viewed as being risky without a widely accepted prediction of financial return. Although different BSS operational strategies have been proposed, an integrated model that considers battery life, lifecycle cost, EV consumer behaviour, and supplementary grid services is still missing. A two-level hierarchical model is proposed where the unit model follows a transition-based battery allocation technique and the station model provides a system-view platform. Based on the designed hierarchical model, the strict grid scheduling strategy and grid scheduling with battery reservation strategy are evaluated in terms of profit and average battery life using New South Wales and South Australia electricity demand profiles. Results suggest that trading short-term grid services profitability in the grid scheduling with battery reservation strategy led to overall increased profit and also longer service life for batteries.

Integrating electric vehicles (EVs) into the smart grid can support various services for the power grid through the vehicle-to-grid (V2G) system. In this study, the effects of critical peaks (CPs) on EVs’ charge/discharge process (CDP) while providing V2G services are critically investigated. A charge/discharge optimisation algorithm for EVs while considering varying charging costs and discharging incentives is proposed. Primarily, a probability model for the occurrence of CPs is formulated and incorporated in a time-of-use tariff plan. Considering the battery capacity loss in a CDP, an optimisation model is developed based on a non-linear programming model. An optimisation algorithm is proposed to enhance the EVs’ CDP. The goal is to obtain the least possible charging cost per day while facilitating the V2G services, especially in case of CPs. The effects of CPs on the per day charging cost while considering real-life scenarios are investigated. Furthermore, the dependence of the energy discharged by the EV on the number of estimated battery cycle life and the per day charging cost considering battery replacement is analysed.

In this study, a double fuzzy control strategy for the parallel hybrid electric vehicle (HEV) is proposed, then based on the genetic algorithm (GA) to get better simulation results, and the results are verified by dynamic programming (DP) optimisation. First, the energy management strategy is established by fuzzy control theory. On this basis, considering braking energy recovery, this study designs a double fuzzy vehicle energy control strategy. A simulation analysis of the above two control strategies is carried out in urban dynamometer driving schedule, and the comparison with the work efficiency of the engine and fuel economy performance, respectively, is made; the simulation results show that the double fuzzy control strategy can effectively improve the HEV performance. In order to make rule base more accurate, this study also uses a GA to optimise the fuzzy control rules of the fuzzy controller. Then the DP is used to optimise the energy control strategy and obtain optimal results. The results verified that the design of fuzzy controllers is correct, and the optimised fuzzy control strategy by GA can improve the work efficiency of the engine and fuel consumption.

Conventional diesel-electric propulsion systems in platform supply vessels (PSVs) use low-voltage AC (LVAC) supply-based architecture with multiple diesel-generators feeding busbars at 690 V, 60 Hz. The busbars distribute power to thruster motor drives via multi-pulse transformers and diode bridge rectifiers. Advancements in electrical power conversion and distribution technologies offer possibilities of AC or DC distribution at low/medium voltage (LV/MV) for reduced fuel consumption (FC), emissions, and equipment footprint. This study presents methodology to qualify propulsion system architecture for PSV application. Potential architectures, besides conventional one, are active front end (AFE) converter-based LVAC (690 V), MVAC (3.3 kV), LVDC (1000 V), and MVDC (5000 V). Performances of these architectures are assessed quantitatively based on FC, emissions, weight, volume, efficiency, and reliability. FC is estimated based on brake-specific FC data of diesel engine. , , and emissions are assessed based on their emission factors. The weight, volume, and efficiency are estimated based on parameters of individual components. Reliability is assessed based on component failure data using DIgSILENT Power Factory. The architectures are ranked based on performance parameters using a Pugh matrix. The most suitable architecture for the target PSV is LVDC, followed by MVDC, LVAC with AFE, MVAC, and conventional LVAC.