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The transport sector is experiencing a shift to zero-carbon powertrains driven by aggressive international policies aiming to fight climate change. Battery electric vehicles (BEVs) will play the main role in passenger car applications, while diversified solutions are under investigation for the heavy-duty sector. Within this framework, Light Commercial Vehicles (LCVs) impact is not negligible and accountable for about 2.5% of greenhouse gas (GHG) emissions in Europe. In this regard, few LCV comparative assessments on green powertrains are available in the scientific literature and justified by the fact that several factors and limitations should be considered and addressed to define optimal powertrain solutions for specific use cases. The proposed research study deals with a comparative numerical assessment of different zero-carbon powertrain solutions for LCV. BEVs are compared to hydrogen-based fuel cells (FC) and internal combustion engines (ICE) powered vehicles.

Laws concerning emissions from heavy duty (HD) internal combustion engines are becoming increasingly stringent. New engine technologies are needed to satisfy these new requirements and to reduce fossil fuel dependency. One way to achieve both objectives can be to partially replace fossil fuels with alternatives that are sustainable with respect to emissions of greenhouse gases, particulates and nitrogen oxides (NOx). A suitable candidate is methanol. The aim of the study presented here was to investigate the possible advantages of combusting methanol in a heavy duty Diesel engine. Those are, among others, lower particulate emissions and thereby bypassing the NOx-soot trade-off. Because of methanol’s poor auto-ignition properties, Diesel was used as an igniting sources and both fuels were separately direct injected. Therefore, two separate standard common rail Diesel injection systems were used together with a newly designed cylinder head and adapted injection nozzles.

In order to avoid the high CO and HC emissions associated with low temperature when using high levels of EGR, partially premixed combustion is an interesting possibility. One way to achieve this combustion mode is to increase the ignition delay by adjusting the inlet valve closing timing, and thus the effective compression ratio. The purpose of this study was to investigate experimentally the possibilities of using late and early inlet valve closure to reduce NOx emissions without increasing emissions of soot or unburned hydrocarbons, or fuel consumption. The effect of increasing the swirl number (from 0.2 to 2.5) was also investigated. The combustion timing (CA50) was kept constant by adjusting the start of injection and the possibilities of optimizing combustion using EGR and high injection pressures were investigated. Furthermore, the airflow was kept constant for a given EGR level.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low.

Combustion characteristics of dimethyl ether, DME, have been investigated experimentally, in a heavy duty single cylinder engine equipped with an adapted common rail fuel injection system, and the effects of varying injection timing, rail pressure and exhaust gas recirculation on the combustion and emission parameters. The results show that DME combustion does not produce soot and with the use of exhaust gas recirculation NOX emissions can also be reduced to very low levels. However, high injection pressure and/or a DME adopted combustion system is required to improve the mixing process and thus reduce the combustion duration and carbon monoxide emissions.

Thermodynamic power cycles have been shown to provide an excellent method for waste heat recovery (WHR) in internal combustion engines. By capturing and reusing heat that would otherwise be lost to the environment, the efficiency of engines can be increased. This study evaluates the maximum power output of different cycles used for WHR in a heavy duty Diesel engine with a focus on working fluid selection. Typically, only high temperature heat sources are evaluated for WHR in engines, whereas this study also considers the potential of WHR from the coolant. To recover the heat, four types of power cycles were evaluated: the organic Rankine cycle (ORC), transcritical Rankine cycle, trilateral flash cycle, and organic flash cycle. This paper allows for a direct comparison of these cycles by simulating all cycles using the same boundary conditions and working fluids.