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This paper presents an analysis for evaluating electric machine and reducer specifications in conjunction with a comprehensive assessment of vehicle dynamics and drivability for an axial flux machine. The refence point for this study is a conventional central drive unit comprising a single electric machine, reducer, and differential. Powertrain architectures configured with two axial flux machines integrated as in-wheel drives as well as one axial flux machine mounted perpendicular to the chassis, are examined in comparison to the reference design. The study begins by establishing wheel-level traction force requirements and minimum power demands for a mid-sized vehicle. Subsequently, requisite machine and reducer specifications are derived based on these findings. Additional considerations encompass packaging constraints and efficiency thresholds.

Recuperated low-pressure-ratio split-cycle engines represent a promising engine configuration for applications like transportation and stand-alone power generation by offering a potential efficiency as high as 60%. However, it can be challenging to achieve the stringent NOx emission standard, such as Euro 6 limit of 0.4 gNOx/kWh, due to the exhaust cylinder high intake temperature. This paper presents experimental investigation of hydrogen-air combustion NOx emissions for such engines for the first time. Experiments are carried out using a simplified constant-volume combustion chamber with glow-plug ignition. Two fuel injection techniques are performed: direct injection and injection via a novel convergent-divergent injector. For the direct injection scenario, NOx levels are unsatisfactory with respect to the Euro 6 standards over a range of operating temperatures from 200 °C to 550 °C.

Modern automotive powertrains are operated using many control devices under a wide range of environmental conditions. The exhaust temperature must be controlled within a specific range to ensure low exhaust-gas emissions and engine-component protection. In this regard, physics-based exhaust-temperature prediction models are advantageous compared with the conventional exhaust-temperature map-based model developed using engine dyno testing results. This is because physics-based models can predict exhaust-temperature behavior in conditions not measured for calibration. However, increasing the computational load to illustrate all physical phenomena in the engine air path, including combustion in the cylinder, may not fully leverage the advantages of physical models for the performance of electric control units (ECUs).

To realize a super-leanburn SI engine with a very-high compression ratio, it is required to design a new fuel which could have low ignitability at a low temperature for antiknocking, but high ignitability at a high temperature for stable combustion. Ethane shows a long ignition delay time at a low temperature close to that of methane, but a short ignition delay time at a high temperature close to that of gasoline. In the present study, the antiknocking effect of adding methane with the RON of 120, ethane with the RON of 108, or propane with the RON of 112 to a regular gasoline surrogate fuel with the RON of 90.8 has been investigated. Adding each gaseous fuel by less than 0.4 in heat fraction advances knocking limit in the descending order of SI timing advance of ethane, methane, and propane, and in the descending order of CA 50 advance of ethane, propane, and methane. Adding methane extends combustion duration slightly, but adding ethane or propane shortens it considerably.

A digital twin is a digital representation of a planned or real physical system, product, or process that functions as its practically identical digital counterpart for tasks such as testing, integration, monitoring, and maintenance. Creating digital twins allows the ‘digital system’ or ‘digital product’ to be tested faster-than-real-time improving overall efficiency and reducing time of a programme. The HORIBA Intelligent Lab virtual engineering toolset was used produce an empirically based digital twin of a contemporary off-highway diesel Internal Combustion Engine (ICE). These empirical models were then coupled with simulations developed by AgriSI and IPG CarMaker to predict performance and emissions for real-world machine handling cycles of off-highway machines such as ploughing, planting, weeding, and fertilising.