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Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive.

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.

Traditionally, Electric Machine design has primarily focused on factors like efficiency, packaging, and cost, often neglecting the critical aspects of Noise, Vibration, and Harshness (NVH) in the early decision-making stages. This disconnect between E-Machine design teams and NVH teams has consistently posed a challenge. This paper introduces an innovative workflow that unifies these previously separate domains, facilitating comprehensive optimization by seamlessly integrating NVH considerations with other E-Machine objectives, such as electromagnetic compatibility (EMC). This paper highlights AVL's approach in achieving this transformation and demonstrates how this integrated approach sets a new standard for E-Machine design. The presented approach relies on AI-driven algorithms and computational tools.

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.

In recent years, the use of high-power inverters has become increasingly prevalent in vehicles applications. With the increasing number of electric vehicle models comes the need for efficient and reliable testing methods to ensure the proper functioning of these inverters. One such method is the use of Hardware-in-the-Loop (HiL) environments, where the inverter is connected to a simulated environment to test its performance under various operating conditions. HiL testing allows for faster and more cost-effective testing than traditional methods and provides a safe environment to evaluate the inverter's response to different scenarios. Further, in such an environment, it is possible to specifically stimulate those system states in which conflicts between the lines arise regarding the ideal system parametrization. By combining HiL testing with design-of-experiments and modelling methods, the propulsion system can hence be optimized in a holistic manner.

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.

The further increase in the efficiency of heavy-duty engines is essential in order to reduce CO2 emissions in the transport sector. This is also valid for the future use of alternative fuels, which can be CO2-neutral, but can cause higher total costs of ownership due to higher prices and limited availability. In addition to thermodynamic optimization, the reduction of mechanical losses is of great importance. In particular, there is a high potential in the piston bore interface, since continuously increasing cylinder pressures have a strong influence on the frictional and lateral piston forces. To meet these future challenges of increasing heavy-duty engine efficiency, AVL has developed a floating liner engine for heavy-duty applications based on its tried and tested passenger car floating liner concept.

Grown interest in complex modern Hybrid Electric Vehicle (HEV) concepts has raised new challenges in the field of NVH. The switch between the Internal Combustion Engine (ICE) and the Electric Motor (EM) at low speeds produces undesirable vibrations and a sudden raise of noise levels that effects the sound quality and passenger comfort achieved by the close-to-silent electric powertrain operation. Starting the ICE in the most suitable driving situation to create a seamless transition between driving modes can be the key to minimize the NVH quality impact in driver and passenger’s perception in HEVs. To integrate this important aspect in the early stages of the development and design phase, simulation technologies can be used to address the customer acceptance. By analyzing NVH measurements, the different noise components of the vehicle operation can be separated into ICE-related noise, EM-related noise and driving noise.

This paper describes the simulation tool chain serving to design and optimize the transmission of an electric axle drive from concept to final design with respect to NVH. A two-stage transmission of an eAxle is designed from scratch by the initial layout of gears and shafts, including the optimization of gear micro geometry. After the shaft system and bearings are defined, the concept design of the transmission housing is evaluated with the help of a basic topology optimization regarding stiffness and certain eigenfrequencies. In the next step a fully flexible multi-body dynamic (MBD) and acoustic analysis of the transmission is performed using internally calculated excitations due to gear contact and bearing interaction with shaft and gear dynamics for the entire speed and load range. Critical operating conditions in terms of shaft dynamics, structure borne noise and noise radiation are evaluated and selected as target for optimization in the following steps.

The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

One of the most important safety issues for automotive engineering is to avoid any fire due to the ignition of flammable liquids, which may result from leaks. Fire risk is a combination of hot temperature, fast vaporisation and accumulation of vapor in a cavity. In IC engines, potentially flammable liquids are fuel and oil. To guarantee safety, flammable liquids must not come into contact with hot parts of the engine. Consequently, shields are designed to guide the flow path of possible leakages and to take any flammable liquid out of the hot areas. Simulation is a great help to optimize the shape of the shield by investigating a large number of possible leakages rapidly. Recent breakthroughs in numerical methods make it possible to apply simulations to industrial design concepts. The employed approach is based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) method.

Spark Ignited (SI) combustions engines in combination with different degrees of hybridization are expected to play a major role in future vehicle propulsion. Due to the combustion principle and the related thermodynamic efficiency, it is especially challenging to meet future CO2 targets. The layout and optimization of the overall system requires novel methods in the development process which feature a seamless transition between real and virtual prototypes. Herein, engine models need to predict the entire engine operating range in steady-state and transient conditions and must respond to all relevant control inputs. In addition, the model must feature true real-time capability. This work presents a holistic and modular modeling framework, which considers all relevant processes in the complex chain of physical effects in SI combustion.

The electrification of the powertrain is a prerequisite to meet future fuel consumption limits, while the internal combustion engine (ICE) will remain a key element of most production volume relevant powertrain concepts. High volume applications will be covered by electrified powertrains. The range will include parallel hybrids, 48V- or High voltage Mild- or Full hybrids, up to Serial hybrids. In the first configurations the ICE is the main propulsion, requiring the whole engine speed and load range including the transient operation. At serial hybrid applications the vehicle is generally electrically driven, the ICE provides power to drive the generator, either exclusively or supporting a battery charging concept. As the ICE is not mechanically coupled to the drive train, a reduction of the operating range and thus a partial simplification of the ICE is achievable.

To achieve future fleet CO2 emission targets, all powertrain types, including those with internal combustion engines, need to achieve higher efficiency. Next to others the reduction of friction is one contributor to increase powertrain efficiency. The piston bore interface (PBI) accounts for up to 50 % of the total engine friction losses [1]. Optimizations in this area combined with the use of low viscosity oil, which can reduce the friction of further engine sub-systems, will therefore have a high positive impact. To assess the friction of the PBI whilst considering cross effects of other relevant parameters for mechanical function (e.g. blow-by & wear) and emissions (e.g. oil consumption) AVL has established a holistic development method based around the AVL FRISC (FRIction Single Cylinder) engine with a floating liner measurement concept.

Faced with the need to reduce development time and cost in view of additional system complexity driven by ever more stringent emission regulations, the Hardware-in-the-Loop (HiL) simulation increasingly proves itself to be an advantageous tool not only in automotive companies but also in the off-road engine industry. The approach offers the possibility to analyze new engine control systems with fewer expensive engine dynamometer experiments and test drives. Thus, development cycles can be shortened and development costs reduced. This paper presents the development of an Internal Combustion Engine (ICE) and the correspondent Exhaust Aftertreatment System (EAS) model, its deployment on a HiL system and its application to pre-calibrate the engine for different vehicle cycles. A zero-dimensional mean value approach was chosen to guarantee adequate real-time factors for the coupling between the models and the Engine Control Unit (ECU).

A growing development of hybrid or fully electrical drives increases the demand for an accurate prediction of noise and vibration characteristics of electric and electronic components. This paper describes the numerical and experimental investigation of noise emissions from power electronics, as one of the new important noise sources in electric vehicles. The noise emitted from the printed circuit board (PCB) equipped with multi-layer ceramic capacitors (MLCC) is measured and used for the calibration and validation of numerical model. Material properties are tuned using results from experimental modal analysis, with special attention to the orthotropic characteristic of the PCB glass-reinforced epoxy laminate sheet (FR-4). Electroacoustic excitation is pre-calculated using an extension of schematic-based EMC simulation and applied to the structural model. Structural vibrations are calculated with a commercial FEM solver with the modal frequency response analysis.

Future legislation scenarios as well as stringent CO2 targets, in particular under real driving conditions, will require the introduction of new and additional powertrain technologies. Beside the increasing electrification of the powertrain, it will be essential to utilize the full potential of the Internal Combustion Engine (ICE). There is clearly a competition of new and different ICE-Technologies [1] including VCR. VCR systems are expected to be introduced to a considerable number of next generation turbocharged Spark Ignited (SI) engines in certain vehicle classes. The implementation of Miller or Atkinson cycles is an essential criterion for increased geometric Compression Ratio (CR). The DUAL MODE Variable Compression System (VCS)TM enables a 2-stage variation of the connecting rod length and thus of the compression ratio (CR).

State-of-the-art motorcycle engines consist of numerous variable components and require a powerful motor management to meet the growing customer expectations and the legislative requirements (e.g. exhaust and noise emissions, fuel consumption) at the same time. These demands are often competing and raise the level of complexity in calibration. In the racing domain, the optimization requirements are usually higher and test efficiency is crucial. Whilst the number of variables to control is growing, the time to perform an engine optimization remains the same or is even shortened. Therefore, simulation is becoming an essential part of the engine calibration optimization. Considering the special circumstances in racing, involving valuable hardware, as well as extremely short development and calibration iteration loops, only transient testing is possible.

Growing development of hybrid and fully electrical drives increases demand for accurate prediction of noise and vibration characteristic of electric and electronic components. This paper describes the numerical and experimental investigation of noise emission from PMSM electric machine as a one of the most important noise sources in electric vehicles. Structural and air borne noise is measured on e-machine test rig and used for calibration and validation of the numerical model. The electro-magnetic field in PMSM is simulated using finite volume method. Electro-magnetic forces are applied as excitation to the 3D FE model of e-machine, mounded on test frame. Material properties are tuned using results from experimental modal analysis including identification of orthotropic characteristic of stator laminated core, assembled together with coil and end winding. Structural vibrations are calculated by modal frequency response analysis and applied as excitation in air borne noise simulation.