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Abstract. With the COP28 decisions the world is thriving for a future net-zero-CO2 society and the and current regulation acts, the energy infrastructure is changing in direction of renewables in energy production. All industry sectors will extend their share of direct or indirect electrification. The question might arise if the build-up of the renewables in energy production is fast enough. Demand and supply might not match in the short- and mid-term. The paper will discuss the roadmaps, directions and legislative boundary parameter in the regenerative energy landscape and their regional differences. National funding on renewables will gain an increasing importance to accelerate the energy transformation. The are often competing in attracting the same know-how on a global scale. In addition the paper includes details about energy conversion, efficiency as well as potential transport scenarios from production to the end consumer.

Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

Vehicle powertrain electrification is considered one of the main measures adopted by vehicle manufacturers to achieve the CO2 emissions targets. Although the development of vehicles with hybrid and plug-in hybrid powertrains is based on existing platforms, the complexity of the system is significantly increased. As a result, the demands of testing during the development and calibration stages is getting significantly higher. To compensate that, high-fidelity simulation models are used as a cost-effective solution. This paper aims to present the methodology followed for the development of a rule-based energy management controller for a plug-in hybrid electric vehicle (PHEV), and to describe the experimental campaign carried out with this passenger car. The controller is implemented in a vehicle simulation model that is parametrized to replicate the operation of the vehicle.

The advent of digitalization opens up new avenues for advances in large internal combustion engine technology. Key engine components are becoming "intelligent" through advanced instrumentation and data analytics. By generating value-added data, they provide deeper insight into processes related to the components. An intelligent common rail diesel fuel injection valve for large engine applications in combination with machine learning allows reliable prediction of key combustion parameters such as maximum cylinder pressure, combustion phasing and indicated mean effective pressure. However, fault-related changes to the injection valve also have to be considered. Based on experiments on a medium-speed four-stroke single-cylinder research engine with a displacement of approximately 15.7 liter, this study investigates the extent to which the intelligent injection valve can improve the reliability of combustion parameter predictions in the presence of injection valve faults.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining modular component technology with integration and industrialization requirements when heading for further significant efficiency optimization. At the same time focus on reduced development time, product cost and minimized additional investment demand reuse of current production, machining, and assembly facilities as far as possible. Up to date additive manufacturing (AM) is an established prototype component, as well as tooling technology in the powertrain development process, accelerating procurement time and cost, as well as allowing to validate a significantly increased number of variants. The production applications of optimized, dedicated AM-based component design however are still limited.

The degradation rate of a Li-ion battery is a complex function of temperature and charge/discharge rates over its lifetime. There is obviously a keen interest in predictive electrochemical ageing models that account for known degradation mechanisms, primarily linked with the Solid Electrolyte Interface (SEI) formation and Li-plating, which are highly dependent on the cell temperature. Typically, such ageing models are formulated and employed at pack or cell level, neglecting intra-cell and cell-to-cell thermal and electrical non-uniformities. On the other hand, thermal management techniques can mitigate ageing by maintaining the battery pack within the desired temperature window either by cooling or heating. Inevitably, the cooling of the battery pack by conventional heat exchangers will introduce temperature non-uniformities that may in turn result in undesired intra-cell and/or cell-to-cell health non-uniformities.

Stoichiometric natural gas (CNG) engines are an attractive solution for heavy-duty vehicles considering their inherent advantage in emitting lower CO2 emissions compared to their Diesel counterparts. Additionally, their aftertreatment system can be simpler and less costly as NOx reduction is handled simultaneously with CO/HC oxidation by a Three-Way Catalyst (TWC). The conversion of methane over a TWC shows a complex behavior, significantly different than non-methane hydrocarbons in stoichiometric gasoline engines. Its performance is maximized in a narrow A/F window and is strongly affected by the lean/rich cycling frequency. Experimental and simulation results indicate that lean-mode efficiency is governed by the palladium’s oxidation state while rich conversion is governed by the gradual formation of carbonaceous compounds which temporarily deactivate the active materials.

India is the market with the highest sales of agricultural tractors and the market with the highest number of agricultural tractor park, as well. Even though taking into account the lower average power of Indian agricultural tractors compared to regions with considerably larger field sizes, their cumulated diesel fuel consumption reaches a significant size. The possible use of alternative powertrains like battery-electric, especially considering the lower power of the Indian tractor market, seems feasible, but might be struggling with challenges in terms of charging infrastructure and the possibly resulting lower productivity due to required charging times. Therefore AVL proposes to investigate the use of alternative fuels for internal combustion engines, a topic which is also being discussed by other global tractor OEMs. In that context the focus is typically on higher tractor powers due to current storage limitations of battery-electric systems and other alternatives.

The internal combustion engine contains several actuators to control engine performance and emissions. These are controlled within the engine ECU and follow a specific operating strategy to achieve objectives such as NOx reduction and fuel economy. However, these two goals are conflicting and a compromise is required. The operating state depends on system constraints such as engine speed, load, temperature levels, and aftertreatment system efficiency. This results in constantly changing target values to stay within the defined limits, especially the legal emission limits. The conventional approach is to use multiple operating modes. Each mode represents a specific compromise and is activated accordingly. Multiple modes are required to meet emissions regulations under all required conditions, which increases the calibration effort. This new control approach uses an artificial neural network to replace the conventional multiple mode approach.

The degradation rate of Li-ion batteries and therefore their useful life depends on many parameters, including temperature, charge/discharge rates, the chemistry and microstructure of electrodes. The importance of understanding these mechanisms explains the large interest in developing predictive electrochemical ageing models accounting for the known deterioration mechanisms, mainly related to SEI layer formation and Li-plating. Usually, these ageing models are developed and applied at cell level assuming perfect uniformity in all dimensions apart from the through-plane direction. In this work, we extend the model to all dimensions within the cell to account for intra-cell non-uniformities in terms of local temperature and current. However, the temperature distribution of a cell within a battery pack depends on the interaction with its environment, which typically involves active cooling via an external fluid circulation within a channel network.

This paper investigates how different on-board energy management system (EMS) algorithms can affect the total energy consumption considering propulsion, heating, ventilation, and air conditioning (HVAC) operation and thermal comfort requirements. Firstly, an integrated plug-in hybrid electric vehicle (PHEV) powertrain and HVAC model including vehicle cabin has been developed as a demonstrator. Two different EMS algorithms - namely a rule-based and an equivalent consumption minimization strategy (ECMS) one - are applied to the integrated PHEV model and evaluated under different environmental conditions. The results showed that the HVAC system operation affects the total energy consumption benefits when ECMS algorithm is used over the rule-based. ECMS reduces the total energy consumption by 2.5% compared to rule-based without HVAC operation, while the total energy consumption reduction changes to 5.3% and 6.3% when HVAC provides heating and cooling power respectively.

To achieve low tailpipe NOX emissions in Heavy-Duty engines, the rapid warm-up of the exhaust aftertreatment system (EAS) needs to be assisted by the adoption of new technologies to reduce engine-out emissions and increase the EAS conversion efficiency. Engine measures like cylinder deactivation, retarded start of the main injection, late intake valve closing, intake throttling and elevated idle speed can substantially increase the available exhaust gas enthalpy and temperature at the expense of additional fuel as has been shown in the literature. On the other hand, the exhaust system can be optimized in terms of hardware and controls, which is nowadays strongly supported by simulation. However, these simulation studies typically assume a fixed engine hardware and calibration and thus fixed engine-out simulation boundary conditions. Moving forward to tougher and real-world oriented legislation, the fixed cycle and engine-out boundary condition becomes insufficient.

The upcoming Euro 7 regulation introduces the concept of continuous On-Board (emission) Monitoring (OBM), while On-Board Fuel/Energy Consumption Monitoring (OBFCM) is already an integral part of modern vehicles. The current work aims to assess whether on-board data could provide sufficient information to characterize real-world vehicle performance and emissions. Nine Euro 6d-ISC-FCM passenger cars were used, covering a wide range of powertrain technologies, from conventional gasoline and diesel to hybrid (HEV) and plug-in hybrid (PHEV) electric vehicles. Three vehicles were thoroughly tested in the laboratory and on the road, aiming at evaluating in detail the on-board data monitoring system. The evaluation concerned OBFCM device recordings of fuel consumed and distance travelled, as well as tailpipe NOx emissions and exhaust mass flow rate.

Increasingly stringent greenhouse gas and emission limits demand for powertrain electrification throughout all vehicle applications. Beside fully electric powertrains different configurations of hybrid powertrains will have an important role in upcoming and future vehicle generations. As already discussed in previous papers, the requirements on the combustion engine in hybrid powertrains are different to those in a conventional powertrain solution, heading for brake thermal efficiency targets of 45% and above within the product lifecycle for conventional fuels. Focus on product cost and production and assembly facility investment drives reuse of technology packages within modular powertrain technology platforms, with different combinations of internal combustion engines (ICE), transmissions, and e-drive-layouts. The goal of zero carbon operation requires compatibility of ICE for sustainable fuels.

Minimizing the lubricant volume in a transmission system reduces the churning losses and overall unit costs. However, lubricant volume reduction is also detrimental to the thermal stability of the system. Transmission overheating can result in significant issues in the region of loaded contacts, risking severe surface/sub-surface damage in bearings and gears, as well as reduction in the lubricant quality through advanced oxidation and shear degradation. The increasing trend of electrified transmission input speeds raises the importance of understanding the thermal limits of the system at the envelope of the performance to ensure quality and reliability can be maintained, as well as being a key factor in the development, effecting internal housing features for the promotion of lubrication. A nodal bearing thermal model will be shown which utilizes thermal resistances and smooth particle based CFD for determining bearing lubricant feed rates during operation.

Biofuels are a promising alternative to fossil fuels as their availability has been reduced during the last decades and they are the main sources of greenhouse gases emissions. Moreover, the targets of the international regulations include reduction of fossil fuels consumption, and improvement of the sustainability of the vehicle fleet. Blending gasoline with biofuels will result in changes in fuel blending procedures and combustion process especially for the gasoline direct injection (GDI) engines. In this article, flame visualization using chemiluminescence techniques in a Single Cylinder Optical Research Engine (SCORE) is presented, with an adjusted intake pressure of 850 mbar and early intake single injection (280 CAD BTDC), by using 100% hydrocarbon-based gasoline, E10 (90% gasoline - 10% ethanol) and ETBE20 (80% gasoline - 20% ethyl tert-butyl ether). ETBE20 is a potential alternative for E10, as it contains the same amount of renewable fuel and has low water solubility.

In Plug in hybrid electric vehicles (PHEVs), the management of the main drivetrain components and the shift between pure electric and hybrid propulsion is decided by the on-board energy management system (EMS). The EMS decisions have a direct impact on CO2 emissions and need to be optimized to achieve as low emissions as possible. This paper presents optimization methods for EMS algorithms of a parallel P2 PHEV. Two different supervisory control algorithms are examined, employing simulations on a validated PHEV platform. An Equivalent Consumption Minimization Strategy (ECMS) algorithm is implemented and compared to a rule-based one, the latter derived by back-engineering of available experimental data. The different EMS algorithms are analyzed and compared on an equal basis in terms of distance, demanded energy and state of charge levels over different driving cycles.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining component technology with integration and industrialization requirements when heading for further significant efficiency optimization of the subsystem internal combustion engine. The requirements on the combustion engine in hybrid powertrains are quite different to those in a conventional powertrain solution. Next-generation hybrid engines, with brake thermal efficiency (BTE) targets starting from 42-43% and aiming for 45% and above within the product lifecycle, require a re-thinking of the base engine architecture of current modular engine platforms. At the same time focus on the product cost and minimized additional investment demand reuse of current production, machining and assembly facilities as far as possible.