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Recent legislation banning the sale of new petrol and diesel vehicles in Europe from 2035 has shifted the focus of internal combustion engine research towards alternative fuels with net zero tailpipe emissions such as hydrogen. Research regarding hydrogen as a fuel is particularly pertinent to the so-called ‘hard-to-electrify’ propulsion applications, requiring a combination of large range, fast refuelling times or high-load duty cycles. The virtual design, development, and optimisation of hydrogen internal combustion engines has resulted in the necessity for accurate predictive modelling of the hydrogen combustion and autoignition processes. Typically, the models for these processes rely respectively on laminar flame speed datasets to calculate the rate of fuel burn as well as ignition delay time datasets to estimate autoignition timing. These datasets are generated using chemical kinetic mechanisms available in the literature.

Plug-in hybrid electric vehicles (PHEVs) have the capability to drive an appreciable fraction of their miles travelled on electric power from the grid, similar to battery-only electric vehicles (BEVs). However, unlike BEVs which cannot drive unless charged, PHEVs can automatically switch to gasoline power and operate similar to a regular (non-plug-in) hybrid electric vehicle (HEV). Though operating similar to HEV is already beneficial in terms of fuel economy, greenhouse gas (GHG) emissions and criteria pollutants compared to conventional internal combustion engine (ICE) vehicles, much of the attractiveness and allure of PHEVs comes from their capability to drive “almost like a BEV”, but without range anxiety about running out of battery charge.

An analytic first-order fuel consumption model is developed for FWD 2-motor HEV vehicles which on average achieve 36% EPA Combined efficiency. The premise of this paper is that this is primarily the result of new functionality specific to HEV. Detailed benchmarking data show that in such an HEV the engine not only provides traction power but simultaneously charges the battery. This combined operation of engine and electric powertrain is unique to HEV and is studied using their linear transfer functions. Charging by the engine enables extended electric driving at low traction power, which reduces engine running time and the associated overhead. The analysis predicts an engine duty cycle proportional to the traction power and inversely proportional to the engine output power: the electric driving is limited by the engine’s ability to deliver the required traction work.

As electrification of powertrains is progressing, diversification of hybrid powertrains increases. This generally imposes the challenge for a supervisory controller of how to optimally control the torque of the electric machine(s). Architectures, which have at least one belt driven electric machine, are an essential part of the portfolio. This paper describes a strategy on how to include the losses of the belt device in the determination of optimal electric machine torque command. It first depicts a physics-based method for controlling optimal electric machine torque command for systems without a belt connected electric machine. This method considers the constraints of the electric machine(s) as well as the power limitations from the electric devices, which supply power to the motors.

Radical greenhouse gases emissions reduction necessity is bringing deep evolution in mobility behaviors and is the core reason for a significant diversification of automotive powertrain technologies, making it more and more complex for customers to find the best suited technology. This paper proposes a customer-oriented approach that translates needs into technical requirements that can be used as choice guidelines. First, customers answer a small survey on their driving habits and the class of car they want. Real life driving cycles are then recorded, and Simulink simulations, based on lowest equivalent consumption calculations, allow to identify and size an ideal powertrain that can then become a benchmark for vehicle final selection.

This paper discusses the dependency between powertrain design and automated driving. The research questions are to what extent automated driving influences the powertrain design and how energy and fuel consumption is affected in comparison to customer driving. For this investigation a concept study is carried out for a D-segment vehicle and multiple powertrain topologies, ranging from non-electrified to plug-in hybrids and battery electric vehicles. In order to answer the research questions, the used development process and the methods for optimizing the drive system are presented accordingly, taking into account all vehicle requirements, the drive system and the components and their interactions with each other. This work focuses on two automated driving functions developed at the Institute of Automotive Engineering of the Technische Universität Braunschweig. The functions are an “automated valet parking” and a “highway pilot”.

Reference velocity (i.e. the absolute velocity of vehicle center of gravity) is a key parameter for vehicle stability control functions as well as for the powertrain control functions of hybrid electric vehicle (HEV). Most reference velocity estimation methods employ the vehicle kinematic and tire dynamic equations to construct high order linear or nonlinear model with a set of parameters and sensor measurements. When using those models, delicate algorithm should be designed to prevent the estimates from deviating along with the increase of nonlinearity, modeling error and noise that introduced by high order, parameter approximation, and sensor measurements, respectively. Alternatively, to improve the function robustness and calibration convenience, a straightforward online estimation method is developed in the paper by using a second-order powertrain dynamic model that only need a small set of vehicle parameters and sensor values.

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.

This paper focuses on an inherent problems of active damping control prevalent in contemporary hybrid torque controls. Oftentimes, a supervisory torque controller utilizes simplified system models with minimal system states representation within the optimization problem, often not accounting for nonlinearities and stiffness. This is motivated by enabling the generation of the optimum torque commands with minimum computational burden. When inherent lash and stiffness of the driveline are not considered, the resulting command can lead to vibrations and oscillations in the powertrain, reducing performance and comfort. The paper proposes a Linear Quadratic Integral (LQI)-based compensator to be integrated downstream the torque supervisory algorithm, which role is to shape transient electric machine torques, compensating for the stiffness and backlash present in the vehicle while delivering the driver-requested wheel torque.

When compared to traditional cars with internal combustion engines (ICEs), electric vehicles (EVs) are seen as a more environmentally friendly option. However, the widespread acceptance of EVs in India faces several obstacles, including the high cost of the technology, inadequate charging infrastructure, and limited driving range. Additionally, potential customers are concerned about the actual range of EVs, which often falls short of the certified range. The certified range is determined based on a standardized driving cycle so selecting the appropriate driving cycle for range estimation is of utmost importance. In India, the modified Indian drive cycle (MIDC) has been implemented, which is comparable to the New European Driving Cycle (NEDC).

Internal combustion (IC) engines still power most of the vehicles on road and will likely to remain so in the near future, especially for heavy duty applications in which electrification is typically more challenging. Therefore, continued improvements on IC engines in terms of efficiency and longevity are necessary for a more sustainable transportation sector. Two important design objectives for heavy duty engines with wet liners are to reduce friction loss and to lower the risks of cavitation damages, both of which can be greatly influenced by the piston-liner clearance and the design of the piston skirt. However, engine design optimization is difficult due to the nonlinear interactions between the key design variables and the design objectives, as well as the multi-physics and multi-scale nature of the mechanisms that are relevant to the design objectives.

A semi-active suspension system provides superior safety, ride, and handling performance for a vehicle by continuously varying the damping based on vehicle motions, where semi-active hydraulic damper (SAHD) is the most critical component. Today, SAHD’s are standard in most of the premium segments of vehicles and optional extras in mid-size and compact vehicle segments. Electric vehicles require larger sized SAHD’s to meet heavier vehicle loads and meet ride and handling requirements. The aim of this paper is to highlight the design and development methodology of a base valve for larger bore-size for semi-active hydraulic damper. The workflow follows to present a process for base valve design to meet structural strength and, the key steps of design calculations of the hydraulic performance. The design of the base valve and suction disks architecture was engineered with the aid of Computer Aided simulations.

As part of the development of its new powertrain consisting of two electric motors, a combustion engine and a gearbox, Renault SAS followed an original approach to achieve an assembly with an optimized, robust, and reliable link between the main electric motor and the gearbox. The running operation optimization as well as the high reliability is achieved by processing the following topics: filtration of vibrations and operating jolts; solving of tribological problems specific to splined connections, such as fretting corrosion and abrasive tooth wear; avoidance of potential seizure of elements with cyclic relative slippage under load; and eventually, control of wear and tear on the sealing and damping O-rings, which must accept oscillating translational movements at the same time as torque transfer. The aim of this article is to retrace the main steps taken to achieve the desired reliability and performance targets for this type of product.

Air pollution from internal combustion engines poses a significant apprehension for both global warming and public health on a worldwide scale. The adoption of hybridization and electrification within the vehicular fleet can help to tackle these challenges. This study evaluates a waste heat recovery system for electric power generation, based on the Inverted Brayton Cycle (IBC) coupled with a high-performance gasoline engine. The Mercedes-Benz CLS 350 CGI engine platform was modelled in AVL Boost software and validated against the reference published experimental data. The engine model was then modified to incorporate the IBC to study the performance of the proposed hybrid propulsion system. The IBC power output was calculated at a wide range of engine speed and load, and results showed that up to 18 kW of extra power output can be generated by the IBC system.

Thermoacoustic heat engines convert heat into useful energy by generating acoustic waves from a heat source that can then be extracted as useful work. These engines are inexpensive, robust, versatile, and capable of extracting energy from a wide variety of heat sources ranging from waste heat from power plants to exhaust heat of vehicles. In this article, our investigation focuses on using simulation workflows to improve the performance of thermoacoustic engines. We begin with validating the workflows with published data for both traveling wave and standing wave thermoacoustic engines. Following that, we investigate the effect of changing the working fluid and the operating pressure to increase acoustic power. This study uses a coupled PowerFLOW™ and PowerTHERM™ methodology to simulate the buoyancy-driven flows that generate acoustic pressure waves. Good correlations were observed for both traveling and standing wave thermoacoustic engines.

To study the heat dissipation performance of the multi-fan cooling module composed of multiple fans and a radiator, numerical models of the radiator and the multi-fan cooling module were established, and heat dissipation performance prediction analysis and application analysis were conducted. In modeling, the Effectiveness-Number of Transfer Units (ε − NTU) method is used to predict the heat dissipation performance of the radiator. The aerodynamic performance of the fan at any speed is obtained by the similarity theorem using the data obtained from the tests at a certain speed. The influence between the fan and the radiator was established by using the flow addition scheme. To validate the established model, heat dissipation performance using 36 radiators and 11 multi-fan cooling modules is measured, and the measured data are compared with the calculations.

Model-based Development (MBD) has been employed for engine development to reconcile the contradictory relationship between numerous functions and systems at a high level and in a short span of time. However, in actuality, as engines have become more advanced, it has become challenging to even satisfy the requirements of individual components. Moreover, reconciling multiple contradictory functions like engine power and strength and durability performance, as well as coordinating many related systems, requires an even higher level of skill. Such harmonization techniques require total optimization studies that cover a wide range of designs, and which requires several years of examination with current development processes. Multi-objective Design Exploration (MODE) methods [1] using parametric models [2] and surrogate models [3] are being used to shorten the development period and achieve more balanced designs.

The context for real-world emissions compliance has widened with the anticipated implementation of EU7 emissions regulations. The more stringent emissions limits and deeper real-world driving test fields of EU7 make compliance more challenging. While EU6 emissions legislation provided clear boundaries by which vehicle and powertrain Original Equipment Manufacturers (OEMs) could develop and calibrate against, EU7 creates additional challenges. To ensure that emissions produced during any real-world driving comply with legal limits, physical testing conducted in-house and in-field to evaluate emissions compliance of a vehicle and powertrain will not be sufficient. Given this, OEMs will likely need to incorporate some type of virtual engineering to supplement physical testing.