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On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

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.

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.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.

Modeling of lithium iron phosphate electrodes calls for appropriate extensions of established model approaches. An electrochemical pseudo two-dimensional and a single-particle model are enhanced to address the phase separating behavior of this material with a variable solid state diffusion model. A particle size distribution model tackles the heterogeneity of the electrode microstructure. Both models are embedded in a framework to describe multi-layer electrode designs featuring segregated material properties. The models are parameterized following literature replicating a good match with measured discharge curves at low, medium and high currents. A simplified version of the rigorous model shows the effort of reparameterization, the computational advantage of model order reduction techniques, the model accuracy and application scope.

An advanced multi-layer material model has been developed to simulate the complex behavior in case-carburized gears where hardness dependent strength and elastic-plastic behavior is characterized. Also, an advanced fatigue model has been calibrated to material fatigue tests over a wide range of conditions and implemented in FEMFAT software for root bending fatigue life prediction in differential gears. An FEA model of a differential is setup to simulate the rolling contact and transient stresses occurring within the differential gears. Gear root bending fatigue life is predicted using the calculated stresses and the FEMFAT fatigue model. A specialized rig test is set up and used to measure the fatigue life of the differential over a range of load conditions. Root bending fatigue life predictions are shown to correlate very well with the measured fatigue life in the rig test.

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.

In view of BS-VI emission norms implementation in Commercial Vehicle (CV) application, the emissions are not only confirmed in standard condition but also in non-standard condition including different combinations of ambient temperature and pressure especially for checking the emission in WNTE cycle. However, achieving the emissions in different environmental conditions require physical emission calibration to be performed in those conditions. Hence, engine must be calibrated in climatic test chambers to ensure emission in different climatic conditions leading to multifold increase in the calibration effort. With addition of BS-VI emission regulation, After Treatment System (ATS) is a mandatory requirement to reduce the tail pipe emissions. Efficient functioning of ATS requires enough heating to convert the engine out emissions. Vehicle level Real Drive Emission (RDE) measurement without Conformity Factor (CF) limitation are added as an important legislative requirement.

India striving for carbon neutrality influences futures powertrain architecture of commercial vehicles. The use of CO2-free drives as battery electric have been demonstrated for various applications. The productivity still is a challenge due to missing high power charging infrastructure or limited range. This draws the attention to the use of sustainable fuels due to lower refueling times. The hydrogen engine got highest attention in the last couple of years. For markets as the EU the driver for hydrogen is the CO2 emission reduction, whereas for markets as India hydrogen offers the additional opportunity for more independence from fossil imports. Different OEMs all over the world have converted diesel engines to hydrogen operation with strong focus on performance and emission demonstration, so far with limited technology readiness of different key components.

The major objective of this paper is to develop thermal management strategy targeting optimum performance of Selective Catalytic Reduction (SCR) catalyst in a Medium Duty Diesel Engine performing in BS6 emission cycles. In the current scenario, the Emissions Norms are becoming more stringent and with the introduction of Real Drive Emission Test (RDE) and WHTC test comprising of both cold and hot phase, there is a need to develop techniques and strategies which are quick to respond in real time to cope with emission limit especially NOx. SCR seems to be suitable solution in reducing NOx in real time. However, there are limitations to SCR operating conditions, the major being the dosing release conditions which defines the gas temperature at which DEF (Diesel Exhaust Fluid) can be injected as DEF injection at lower gas temperatures than dosing release will lead to Urea deposit formation and will significantly hamper the SCR performance.

Brake wear emissions gained significant relevance with the upcoming Euro7 type approval within the European Union for brake emission measurement on the test bed. While the controlled brake test bed approach provides consistent results, real-driving emission (RDE) measurements are needed to better understand actual emission behavior due to varying vehicle and environmental conditions. The EU has already announced its interest in RDE testing. Here we present the results of an RDE brake wear sampling system with minimal thermal impact, where particles are only sampled from one side of the brake disc, characterized on a laboratory sampling system. The investigations aim to validate symmetric particle release and to confirm that doubling the measured RDE results effectively represents the reference emissions on the test bed.

Non-exhaust emissions are clearly one of the focal points for the upcoming Euro 7 legislation. The new United Nations Global Technical Regulation (UN GTR) defining the framework for brake emission measurements is about to be officially published. The first amendment to this text is already on the way through the United Nations Economic Commission for Europe (UNECE) hierarchy for decision making. In real life, the final emission factor as the ultimate result of a test is influenced by inaccuracies of numerous parts of the measurement system as well as additional contributing factors like the performance of the particulate filter handling process, which might not be primarily related to equipment specifications.

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.

Hydrogen promises to provide some highly desired features for clean and efficient combustion, but harvesting efficiency and emission potentials as well as meeting engine durability requirements needs careful adaption of both, combustion system components and engine operation strategies. Key points for H2-ICE combustion are some specific and unique features of H2/air mixtures, among which – to name only a few – excellent dilutability, lean burn capability, low ignition energy and high molecular diffusivity and their consequences on ICE operation do play prominent roles. H2 admission via port or direct injection, compression ratio selection and injection timing provide a set of parameters to control combustion features.

Within gear pair development, the simulation of loaded transmission error, line of action and summarized mesh point are crucial information in design optimization as well as reliability, NVH and efficiency prediction. These properties and variables are difficult to evaluate and are usually only assessed through proxy-variables such as unloaded transmission error or contact pattern assessment. Alternatively, large design loops can be generated when prototypes are produced to directly assess the results of reliability, NVH and efficiency and simulation models updated to the results, but not directly calibrated. This work will showcase an advanced test facility with the unique capabilities to evaluate all gear contact types (including hypoid, beveloid, cylindrical and spiral) under loaded conditions while assessing position and force data that can be used to validate simulation models directly and enhance design development.

This work elaborates the transferability of electrode diffusion coefficients gained from fitting procedures in frequency domain to an electrochemical battery model run in time domain. An electrochemical battery model of an NMC622 half-cell electrode is simulated with sinusoidal current excitations at different frequencies. The current and voltage signals are analyzed in frequency domain via Nyquist and Bode plots. The frequency domain analysis of time domain simulations is applied to assess the numerical convergence of the simulation and the sensitivity on particle diameter, electrode and electrolyte diffusion coefficients. The simulated frequency spectra are used to fit the electrode diffusion coefficient by means of different electrical equivalent circuit models and the electrochemical battery model itself. The fitted diffusion coefficients from the different electrical equivalent circuit models deviate by one order of magnitude from the a priori known reference data.

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.

As electrified powertrains trends towards the new norm in development, the need to consider modular development approaches becomes more prevalent. Modular system developments seek to offer an adaptable product range by considering each system component (transmission, e-motor, inverter, battery, etc.) and system element (park-lock, disconnect, differential, etc.) as interchangeable. This can result in a lower cost development process overall to increase the returns for tier1 suppliers by expanding the marketability of the platform. Such an approach has hitherto held relatively low commercial interest as the rate of technological advancement negated the benefits of a modular development due to the lack of long-term competitivity. Previously large technological advances between successive productions and the relatively limited EV market, centred around SUV and small car applications, reduced the value in committing to a platform development.

Fully flexible dual fuel (DF) internal combustion (IC) engines, that can burn diesel and gas simultaneously, have become established among heavy-duty engines as they contribute significantly to lower the environmental impact of the transport sector. In order to gain better understanding of the DF combustion process and establish an effective design methodology for DFIC engines, high fidelity computational fluid dynamics (CFD) simulation tools are needed. The DF strategy poses new challenges for numerical modelling of the combustion process since all combustion regimes have to be modelled simultaneously. Furthermore, DF engines exhibit higher cycle-to-cycle variations (CCV) compared to the pure diesel engines. This issue can be addressed by employing large eddy simulation coupled with appropriate DF detailed chemistry mechanism. However, such an approach is computationally too expensive for today’s industry-related engine calculations.