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For the purpose of achieving carbon-neutrality in the mobility sector by 2050, hydrogen can play a crucial role as an alternative energy carrier, not only for direct usage in fuel cell-powered vehicles, but also for fueling internal combustion engines. This paper focuses on the numerical investigation of high-pressure hydrogen injection and the mixture formation inside a high-tumble engine with a conventional liquid fuel injector for passenger cars. Since the traditional 3D-CFD approach of simulating the inner flow of an injector requires a very high spatial and temporal resolution, the enormous computational effort, especially for full engine simulations, is a big challenge for an effective virtual development of modern engines. An alternative and more pragmatic lagrangian 3D-CFD approach offers opportunities for a significant reduction in computational effort without sacrificing reliability.

Heavy duty truck engines are quite difficult to electrify, due to the large amount of energy required on-board, in order to achieve a range comparable to that of diesels. This paper considers a commercial 6-cylinder engine with a displacement of 12.8 L, developed in two different versions. As a standard diesel, the engine is able to deliver more than 420 kW at 1800 rpm, whereas in the CNG configuration the maximum power output is 330 kW at 1800 rpm. Maintaining the same combustion chamber design of the last version, a theoretical study is carried out in order to run the engine on Hydrogen, compressed at 700 bar. The study is based on GT-Power simulations, adopting a predictive combustion model, calibrated with experimental results. The study shows that the implementation of a combustion system running on lean mixtures of Hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the CNG engine.

The global transportation industry, and road freight in particular, faces formidable challenges in reducing Greenhouse Gas (GHG) emissions; both Europe and the US have already enabled legislation with CO2 / GHG reduction targets. In Europe, targets are set on a fleet level basis: a CO2 baseline has already been established using Heavy Duty Vehicle (HDV) data collected and analyzed by the European Environment Agency (EEA) in 2019/2020. This baseline data has been published as the reference for the required CO2 reductions. More recently, the EU has proposed a Zero Emissions Vehicle definition of 3g CO2/t-km. The Zero Emissions Vehicle (ZEV) designation is expected to be key to a number of market instruments that improve the economics and practicality of hydrogen trucks. This paper assesses the permissible amount of carbon-based fuel in hydrogen fueled vehicles – the Pilot Energy Ratio (PER) – for each regulated subgroup of HDVs in the baseline data set.

The transition from ICE to electric power trains in new vehicles along with the application of advanced active and passive noise reduction solutions has intensified the perception of noise sources not directly linked to the propulsion system. This includes road noise as amplified by the tire cavity resonance. This resonance mainly depends on tire geometry, air temperature inside the tire and vehicle speed and is increasingly audible for larger wheels and heavier vehicles, as they are typical for current electrical SUV designs. Active technologies can be applied to significantly reduce narrow band tire cavity noise with low costs and minimal weight increase. Like ANC systems for ICE powertrains, they make use of the audio system in the vehicle. In this paper, a novel low-cost system for road induced tire cavity noise control (RTNC) is presented that reduces the tire cavity resonance noise inside a car cabin.

The benefits introduced by the replacement of conventional centrifugal pumps with volumetric machines for Internal Combustion Engines (ICEs) cooling were experimentally and theoretically proven in literature. In particular, Sliding Rotary Vane Pumps (SVRPs) ensure to achieve an interesting reduction of ICEs fuel consumption and CO2 emissions. Despite volumetric pumps are a reference technology for ICE lubrication oil circuits, the application in ICE cooling systems still not represent a ready-to-market solution. Particularly challenging is the case of Heavy-Duty ICE due to the wide operating range the pump covers in terms of flow rate delivered. Generally, SVRPs are designed to operate at high speeds to reduce machine dimensions and, consequently, the weight. Nevertheless, speed increase could lead to a severe penalization of pump performance since the growth of the friction losses.

Heavy-duty vehicles equipped with polymer electrolyte membrane fuel cells (PEM-FC) are an environmentally friendly alternative to vehicles powered by internal combustion engines. A major challenge for heavy-duty fuel cell vehicles is the potential cooling deficit under high load conditions at high ambient temperatures. To solve this problem, a spray cooling system can be utilized, in which liquid water is sprayed on the main cooler at the front end of the vehicle. The evaporation of the sprayed liquid water results in an increased cooling power. In this paper, the recovery of liquid water within the cathode loop of a mobile PEM-FC system is presented and discussed. For this purpose, three different topologies of the cathode subsystem of the PEM-FC are investigated for recovering liquid water directly from the fuel cell exhaust gas. To obtain liquid water, vapor in the exhaust gas is cooled below the saturation temperature in an additional heat exchanger.

Planning for charging in transport missions is vital when commercial long-haul vehicles are to be electrified. In this planning, accurate range prediction is essential so the trucks reach their destinations as planned. The rolling resistance significantly influences truck energy consumption, often considered a simple constant or a function of vehicle speed only. This is, however, a gross simplification, especially as the tire temperature has a significant impact. At 80 km/h, a cold tire can have three times higher rolling resistance than a warm tire. A temperature-dependent rolling resistance model is proposed. The model is based on thermal networks for the temperature at four places around the tire. The model is tuned and validated using rolling resistance, tire shoulder, and tire apex temperature measurements with a truck in a climate wind tunnel with ambient temperatures ranging from -30 to 25 °C at an 80 km/h constant speed.

This study focuses on the operation of trolley-assisted mining truck, which leverage overhead lines for uphill propulsion, substantially reducing fuel consumption and carbon emissions. The pantograph mounted at the truck body's front exhibits complex vibrational behavior due to the subgrade stiffness and the nonlinearities of the hydro-pneumatic suspension. Vertical dynamic model of the mining truck is constructed which considering the road conditions and suspension characteristics to illustrate the pantograph's contact force. The vibration characteristic of pantograph base is analyzed which using the spatial transformation relationship between the truck's center mass of gravity and the base of pantograph. The stiffness of pantograph is designed based on a pantograph-catenary system model considering different road conditions. The real mining truck is modeled in the Trucksim software to obtain the vibration of pantograph base.

The work examined the practicality of converting a modern production 6 cylinder 7.7 litre heavy-duty diesel engine for flex dual-fuel operation with ammonia as the main fuel. A small amount of diesel fuel (pilot) was used as an ignition source. Ammonia was injected into the intake ports during the intake stroke, while the original direct fuel injection equipment was retained and used for pilot diesel injection. A bespoke engine control unit was used to control the injection of both fuels and all other engine parameters. The aim was to provide a cost-effective retrofitting technology for existing heavy-duty engines, to enable eco-friendly operation with minimal carbon emissions. The tests were carried out at a baseline speed of 600 rpm for the load range of the engine (10-90%), with minimum pilot diesel quantity and as high as 90% substitution ratio of ammonia for diesel fuel.

Ammonia is one of the carbon-free alternatives considered for power generation and transportation sectors. But ammonia’s lower flame speed, higher ignition energy, and higher nitrogen oxides emissions are challenges in practical applications such as internal combustion engines. As a result, modifications in engine design and control and the use of a secondary fuel to initiate combustion such as natural gas are considered for ammonia-fueled engines. The higher-octane number of methane (the main component in natural gas) and ammonia allows for higher compression ratios, which in turn would increase the engine's thermal efficiency. One simple approach to initiate and control combustion for a high-octane fuel at higher compression ratios is to use a spark plug. This study experimentally investigated the operation of a heavy-duty compression ignition engine converted to spark ignition and ammonia-methane blends.

In 2022 in the UK, the transport sector was the largest single contributing sector to greenhouse gas emissions, responsible 34% of all territorial carbon dioxide emissions [1]. In the UK there is growing uptake in zero emission powertrain technologies, with the most promising variants based on battery electric or hydrogen fuel cell electric configurations. Given the limited number of fuel cell electric buses currently in operation in Europe, vehicle models and simulations are one of the few methods available to estimate energy consumption and provide the necessary increased confidence in operating range. This paper investigates the impact of route characteristics, thermal demand and coefficient of performance of different heat source configurations on the operational energy consumption of fuel cell electric buses. Using a MATLAB/Simulink model, the total energy demand of a vehicle operating in different route/elevation profiles is considered.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

In order to study the influence of engine silicone oil fan clutch on the performances of engine cooling system under different control strategies, a model of engine cooling system for light truck is established. The working characteristics of the silicone oil clutch and the measured performance parameters of the cooling system components are taken into account in our proposed model. Modeling methods for different silicone oil fan control strategies are also given. Using the established model, the performance parameters under different vehicle speeds, such as coolant temperature of engine outlet and power consumption of cooling fan, are calculated and analyzed. The in-suite measurement of the engine cooling system is carried out to get the temperatures of engine coolant inlet and outlet from engine ECU. The model is validated by the comparison between the calculation and the measured results.

Multi-motor powertrain topologies are playing an increasingly important role in the development of heavy duty battery electric trucks due to the changing driving requirements of these vehicles. The use of multiple motors and/or transmissions in a powertrain provides additional degrees of freedom for the energy management. The energy management system (EMS) consist of the gear selection strategy and torque split between the drive motors. The aim of the EMS is thereby to achieve high energy efficiency in motor and regenerative operation, while reducing the number of gear changes to ensure driving comfort. Ongoing research focuses on the energy management system of hybrid electric trucks, where the aim is to optimize the torque split between the combustion engine and the electric motor. In this paper, the EMS for an electric truck is described as a mixed-integer nonlinear control problem. This type of optimal control problem is notoriously difficult to solve.

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.

Diesel-fueled heavy-duty vehicles (HDVs) can be retrofitted with conversion kits to operate as dual-fuel vehicles in which partial diesel usage is offset by a gaseous fuel such as compressed natural gas (CNG). The main purpose of installing such a conversion kit is to reduce the operating cost of HDVs. Additionally, replacing diesel partially with a low-carbon fuel such as CNG can potentially lead to lower carbon dioxide (CO2) emissions in the tail-pipe. The main issue of CNG-diesel dual-fuel vehicles is the methane (CH4, the primary component of CNG) slip. CH4 is difficult to oxidize in the exhaust after-treatment (EAT) system and its slip may offset the advantage of lower CO2 emissions of natural gas combustion as CH4 is a strong greenhouse gas (GHG). The objective of this study is to compare the emissions of an HDV with a CNG conversion kit operating in diesel and dual-fuel mode during highway operation.

A potential route to reduce CO2 emissions from heavy-duty trucks is to combine low-carbon fuels and a hybrid-electric powertrain to maximize overall efficiency. A hybrid electric powertrain can reduce the peak power required from the internal combustion engine, leading to opportunities to reduce the engine size but still meet vehicle performance requirements. Although engine downsizing in the light-duty sector can offer significant fuel economy savings mainly due to increased part-load efficiency, its benefits and downsides in heavy-duty engines are less clear. As there has been limited published research in this area to date, there is a lack of a standardized engine downsizing procedure.

This paper presents an optimal control co-design framework of a parallel electric-hydraulic hybrid powertrain specifically tailored for heavy-duty vehicles. A pure electric powertrain, comprising a rechargeable lithium-ion battery, a highly efficient electric motor, and a single or double-speed gearbox, has garnered significant attention in the automotive sector due to the increasing demand for clean and efficient mobility. However, the state-of-the-art has demonstrated limited capabilities and has struggled to meet the design requirements of heavy-duty vehicles with high power demands, such as a class 8 semi-trailer truck. This is especially evident in terms of a driving range on one battery charge, battery charging time, and load-carrying capacity. These challenges primarily stem from the low power density of lithium-ion batteries and the low energy conversion efficiency of electric motors at low speeds.

Internal combustion engines are becoming ever more efficient as mankind seeks to mitigate the effects of climate change while still maintaining the benefits that a mechanized society has brought to the global economy. As peak values, mass production spark-ignition engines can now achieve approximately 40% brake thermal efficiency and heavy-duty truck compression-ignition engines can approach 50%. While commendable, the unfortunate truth is that the remainder gets emitted as waste heat and is sent to the atmosphere to no useful purpose. Clearly, if one could recover some of this waste heat for beneficial use then this is likely to become important as new means of mitigating fossil CO2 emissions are demanded. A previous study by the authors has identified that the closed Joule cycle (or complications of it beginning to approximate the closed Ericsson cycle) could reasonably be developed to provide a practical means of recovering exhaust heat when applied to a large ship engine.

The thermal behavior of the electric axle is an essential indicator which requires certain attention during the development process. Due to the complexity of heat generation mechanism and heat transfer boundary conditions, it is difficult to accurately predict the axle’s temperature, especially in real driving conditions. In this paper, a comprehensive 1D model is developed to simulate its heat transfer process effectively and accurately. The heat transfer model is developed based on the thermal network method, and the electric axle is divided into thermal mass according to its heat transfer characteristics. The heat generation model, which accounts for meshing loss, bearing loss, churning loss, and windage loss, exchanges heat flux and oil temperature information with the heat transfer model to take into account the effect of lubricating oil temperature on power loss.