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With the increasing importance of electrified powertrains, electric motors and gear boxes become an important NVH source especially regarding whining noises in the high frequency range. Engine encapsulation noise treatments become often necessary and present some implementation, modeling as well as optimization issues due to complex environments with contact uncertainties, pass-throughs and critical uncovered areas. Relying purely on mass spring systems is often a too massive and relatively unefficient solution whenever the uncovered areas are dominant. Coverage is key and often a combination of hybrid backfoamed porous stiff shells with integral foams for highly complex shapes offer an optimized trade-off between acoustic performance, weight and costs.

Meta material has been known for many years and the physics are well known since decades. But the challenge has always been to put the know how into (mass) production. This was the reason why no meta material has found its way into the automotive industry so far. But now things have changed: meta material became Meta Design and is going into serial production in 2024. Meta Design is a tunable spring mass system with foam acting as the spring and heavy layer as the mass. Meta Design is characterized by cavities in the foam and concentrated masses of the heavy layer as functionalized mass pins. By tuning the size of the cavities and the weight of the mass pins the acoustic performance can be adjusted to the requirements of each individual car line. After preliminary simulations, flat samples were tested in the lab. The next step was launched: the production and testing of a handmade prototype part of a firewall insulation for a Mercedes-Benz A-Class.

Although structural intensity was introduced in the 80's, this concept never found practical applications, neither for numerical nor experimental approaches. Quickly, it has been pointed out that only the irrotational component of the intensity offers an easy interpretation of the dynamic behavior of structures by visualizing the vibration energy flow. This is especially valuable at mid and high frequency where the structure response understanding can be challenging. A new methodolodgy is proposed in order to extract this irrotational intensity field from the Finite Element Model of assembled structures such as Bodies In White. This methodology is hybrid in the sense that it employs two distinct solvers: a dynamic solver to compute the structural dynamic response and a thermal solver to address a diffusion equation analogous to the thermal conduction built from the previous dynamic response.

In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles re-quire larger refrigerant compressors, as the battery and the electric motors must be cooled in addition to the interior. The compressor causes the acoustic excitation of other refrigeration circuit components and the chassis via pressure pulsations and vibration transmission, as well as emitting airborne sound directly. Sound measurements have been performed in an anecho-ic chamber to investigate the influence of operating conditions on the acoustics of an electric scroll compressor. This paper investigates the influence of the operating conditions on com-pressor acoustics and shows that rotation speed is the main factor influencing compressor noise. The sound spectra of fluid, structure and airborne noise are dominated by speed-dependent, tonal components.

As environmental concerns have taken the spotlight, electrified powertrains are rapidly being integrated into vehicles across various brands, boosting their market share. With the increasing adoption of electric vehicles, market demands are growing, and competition is intensifying. This trend has led to stricter standards for noise and vibration as well. To meet these requirements, it is necessary to not only address the inherent noise and vibration sources in electric powertrains, primarily from motors and gearboxes, but also to analyze the impact of the spline power transmission structure on system vibration and noise. Especially crucial is the consideration of manufacturing discrepancies, such as pitch errors in splines, which various studies have highlighted as contributors to noise and vibration in electric powertrains. This paper focuses on comparing and analyzing the influence of spline pitch errors on two layout configurations of motor and gearbox spline coupling structures.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

The current automotive industry has a growing demand for real-time transmission to support reliable communication and for key technologies. The Time-Sensitive Networking (TSN) working group introduced standards for reliable communication in time-critical systems, including shaping mechanisms for bounded transmission latency. Among these shaping mechanisms, Cyclic Queuing and Forwarding (CQF) and frame preemption provide deterministic guarantees for frame transmission. However, despite some current studies on the performance analysis of CQF and frame preemption, they also need to consider the potential effects of their combined usage on frame transmission. Furthermore, there is a need for more research that addresses the impact of parameter configuration on frame transmission under different situations and shaping mechanisms, especially in the case of mechanism combination.

Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration.

The automatic transmission of a specialized vehicle encountered challenges in achieving stable oil filling time due to the considerable variability of related parameters and the non-linear trends in the variation of individual product parameters over time. To investigate the underlying causes of this phenomenon and enhance the oil filling efficiency, a detailed model of the clutch oil filling process during gear shifting was established in this paper, which included dynamic models of the key components such as the hydraulic system, clutch, proportional valve, and oil passages. Physical experiments were performed on the test bench to compare with the simulation results. The results showed that the correlation between the simulation model and the test bench was well, which verified the effectiveness of the simulation model.

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations.

Recently, as part of the effort to enhance fuel efficiency and reduce costs for eco-friendly vehicles, the R-gearless system has been implemented in the TMED (P)HEV system. Due to the removal of the reverse gear, a distinct backward driving method needs to be developed, allowing the Electronic Motor (e-Motor) system to facilitate backward movement in the TMED (P)HEV system. However, the capability of backward driving with the e-Motor is limited because of partial failure in the high-voltage system of an R-gearless system. Thus, we demonstrate that it is possible to improve backward driving problems by applying a new fail-safe strategy. In the event of a high-voltage battery system failure, backward driving can be achieved using the e-Motor with constant voltage control by the Hybrid Starter Generator (HSG), as proposed in this study.

The rapid evolution of battery electric vehicle (BEV) development has highlighted the need to develop BEVs that meet customer demands for both high-performance and space-efficiency. This paper explores the optimization opportunities available within the landscape of BEV powertrains, focusing on the power-dense potential of single-axis powertrain systems. The need to adhere to power density requirements to accommodate performance aspirations while simultaneously yielding more cabin or storage space to the customer creates a challenging problem for designers. With this pursuit, these competing interests must strike a harmonious balance to create the best experience for the customer. The subject of this study is an investigation into a leading competitor's powertrain that explores the potential optimization opportunities available within its already compact single-axis electric transmission.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.

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.

This paper proposes an optimization-based transmission gear shifting strategy for electrified powertrains with a transmission. With the demand for reduced vehicle emissions, electrified propulsion systems have garnered significant attention due to their potential to improve vehicle efficiency and performance. An electrified propulsion system architecture of significance includes multiple electric motors and a transmission where some driveline actuators can transmit torque through changing gear ratios. If there is at least one electric motor arranged before the input of the transmission and at least one after the transmission output, a unique design opportunity arises to shift gears in the most energy efficient manner.

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.

This paper presents a feedback control strategy to minimize noise during dog clutch engagement in a hybrid transmission. The hybrid transmission contains an internal combustion engine(ICE) and 2 electric motors in P1 and P3 configurations. For efficiency during driving, at high vehicle speeds ICE is connected to wheels, via the dog clutch, hence shifting the vehicle from series to parallel hybrid mode. It is shown by experimental results that if the speed difference between the two sides of the dog clutch is below a certain level the engagement will be without clonk noise. In this paper the designed state feedback Linear Quadratic Integral (LQI) control provides the synchronization torque request to the P1 motor, hence matching the speed of one side of dog clutch with the other under the disturbance from combustion torque of the engine.

In torque converters, a lockup clutch is used for direct torque transfer from the engine to the gearbox. Nowadays, earlier lockup engagement is necessary to reduce fuel consumption. It introduces noise and vibration issues in the transmission that are solved by clutch slipping. However, the clutch experiences much heat because of earlier engagement, which needs to be adequately dissipated by ATF oil. To overcome this issue, multi-plate clutches are commonly used for efficient torque transfer and clutch slipping. On the other side, packaging space for torque converters is reducing at the vehicle level, especially in hybrid vehicles, which reduces the efficient cooling of clutches. So, accurate modeling of clutch slipping is necessary to improve the clutch performance and durability of the product. Clutch slipping is a transient phenomenon that involves conjugate heat transfer and rotational flow modeling. There are different ways to model clutch slipping in CFD simulations.

Recently, there has been a new method for setting bearing preload on tapered roller bearings in a power transmission system. To move this new method into production, an analytical model that relates the bearing preload to the stiffness of the bearing was developed. This work develops an analytical model that links the preload on multi-row tapered roller bearings to the stiffness of the power transmission system. This study also validates the proposed analytical model by comparing it to both previous work and commercially available simulation software. The analytical model has shown that it is highly sensitive to the number of rollers in the bearing, which is discussed in this work.