Industrial applications such as automation, robots, and electric vehicles are widely employing permanent magnet synchronous motors (PMSM) due to inherent characteristics such as high torque to power ratio, low maintenance, high efficiency, and wide operating range. However, PMSM drives can suffer from unwanted torque ripples caused by periodic disturbances of the electromagnetic effect. First, this article analyzes the sources of torque ripple in PMSMs. Second, the torque measurement techniques of the PMSM including torque sensors, torque observers, and indirect measurement methods are discussed to highlight their shortcomings. Third, this article categorizes and summarizes advanced control-based torque ripple minimization (CB-TRM) techniques for the PMSM by critically evaluating their impacts. These CB-TRM techniques actively control the current waveforms to ensure smooth torque generation and mitigate the effects of torque ripples. Finally, the article concludes by discussing remaining research questions and opportunities for future research on TRM techniques for PMSMs.

This paper was published in the journal Energy Conversion and Management and the definitive published version is available at https://doi.org/10.1016/j.enconman.2016.12.033.The electrification of engine components offers significant opportunities for fuel efficiency improvements. The electrified turbocharger is one of the most attractive options since it recovers part of the engine exhaust gas mechanical energy to assist boosting. Therefore, the engine can be downsized through improved transient responsiveness. In the electrified turbocharger, an electric machine is mounted on the turbine shaft and changes the air system dynamics, so characterisation of the new layout is essential. A systematic control solution is required to manage energy flows in the hybrid system. In this paper, a framework for characterisation, control, and energy management for an electrified turbocharged diesel engine is proposed. The impacts of the electric machine on fuel economy and air system variables are analysed. Based on the characterisation, a two-level control structure is proposed. A real-time energy management strategy is employed as the supervisory level controller to generate the optimal values of critical variables, while a model-based multi-variable controller is designed as the low level controller to track the values. The two controllers work together in a cascade to address both fuel economy optimisation and battery state-of-charge maintenance. The proposed control strategy is validated on a high fidelity physical engine model. The tracking performance shows the proposed framework is a promising solution in regulating the behavior of electrified engines

The integration of selective catalytic reduction catalysts (SCR) into diesel particulate filters (DPF) as a way to treat nitrogen oxides (NOx) and particulate matter (PM) emission is an emerging technology in diesel exhaust aftertreatment. This is driven by ever-tightening limits on NOx and PM emission. In an integrated SCR-in-DPF (also known as SCRF®, SCR-on-DPF, SDPF, or SCR coated filter), the SCR catalyst is impregnated within the porous walls of the DPF. The compact, low weight/volume of the integrated unit provides improvement in the diesel engine cold start emission performance. Experimental investigations have shown comparable performance with standard SCR and DPF units for NOx conversion and PM control, respectively. The modelling of the integrated unit is complicated. The main challenge is how to best capture the complexity of the physical phenomena-e.g., the competition of soot oxidation and SCR reaction for available NO2, or the interaction of washcoat loading on deNOx performance, PM filtration efficiency and system pressure drop-in a simplified but adequate representation. This paper reviews the approaches to SCR-in-DPF modelling obtained from published materials. It discusses the specific considerations given to adapting coated (catalysed) DPF model for SCR-in-DPF modelling. This includes characterisation of SCR model and associated kinetics, inclusion of ammonia dynamics and interaction with soot in the transport model, and careful model calibration to capture the salient phenomena in the system. This work presents current research in SCR-in-DPF modelling and highlights potential areas of future research. It can serve as a resource for new researchers in SCR-in-DPF modelling

As the market share of electric vehicles increases, the intermittent load on the electricity grid due to charging will increase. This can be counteracted by Vehicle-to-Grid (V2G) which utilises dormant electric vehicles to feed power into the grid, generating income for the vehicle owner while relieving load across the grid. However, increased battery use through V2G can negatively affect battery health. In this work, a computational model of an electric vehicle with battery degradation is used to investigate the relationship of these effects. The analysis was conducted at the top level of detail, only considering the battery pack of the vehicle. The findings of this investigation show that the cost relating to battery degradation is smaller than the potential profit available from Vehicle-to-Grid over a three-year period. However, the benefit does not seem to be enough to justify the upfront investment requirement, and further financial incentives, such as net billing, may be required to make V2G economically viable. Future development within this field is vital for the success of the electric vehicle within the automotive markets, and for the transition to a renewable energy grid.

Electrical turbocharger assist is one of the most critical technologies in improving fuel efficiency of conventional powertrain vehicles. However, strong challenges lie in high efficient operations of the device due to its complexity. In this paper, an integrated framework on characterization, control, and testing of the electrical turbocharger assist is proposed. Starting from a physical characterization of the engine, the controllability and the impact of the electrical turbocharger assist on fuel economy and exhaust emissions are both analyzed. A multivariable robust controller is designed to regulate the dynamics of the electrified turbocharged engine in a systematic approach. To minimize the fuel consumption in real time, a supervisory level controller is designed to update the setpoints of key controlled variables in an optimal way. Furthermore, a cutting-edge experimental platform based on a heavy-duty diesel engine is built. The proposed framework has been evaluated in simulations, physical simulations, and experiments. Results are presented for the developed system and the proposed framework that demonstrate excellent tracking performance, high robustness, and the potential for improvements in fuel efficiency.

A high-redundancy actuator (HRA) is an actuation system composed of a high number of actuation elements, increasing both travel and force above the capability of an individual element. This approach provides inherent fault tolerance: if one of the elements fails, the capabilities of the whole actuator may be reduced, but it retains core functionality. Many different configurations are possible, with different implications for the actuator capability and reliability. This article analyses the reliability of the HRA based on the likelihood of an unacceptable reduction in capability. The analysis of the HRA is a highly structured problem, but it does not fit into known reliability categories (such as the k-out-of-n system), and a fault-tree analysis becomes prohibitively large. Instead, a multi-state systems approach is pursued here, which provides an easy, concise and efficient reliability analysis of the HRA. The resulting probability distribution can be used to find the optimal configuration of an HRA for a given set of requirements.