Browse Topic: Engine cylinders
Reducing vehicle weight is a key task for automotive engineers to meet future emission, fuel consumption, and performance requirements. Weight reduction of cylinder head and crankcase can make a decisive contribution to achieving these objectives, as they are among the heaviest components of a passenger car powertrain. Modern passenger car cylinder heads and crankcases have greatly been optimized in terms of cost and weight in all-aluminum design using the latest conventional production techniques. However, it is becoming apparent that further significant weight reduction cannot be expected, as processes such as casting have reached their limits for further lightweighting due to manufacturing restrictions. Here, recent developments in the additive manufacturing (AM) of metallic structures is offering a new degree of freedom. As part of the government-funded research project LeiMot [Lightweight Engine (Eng.)] borderline lightweight design potential of a passenger car cylinder head with the use of automated structural optimization is investigated. A four-cylinder 2.0 L series production Diesel engine cylinder head is taken as basis in terms of bolting and gas flow channels. With the newly gained design freedom by AM, it is demonstrated that a cylinder head with up to 30% weight reduction in comparison to the reference cylinder head can be realized through a novel stiffness concept, while fulfilling the mechanical requirements. The optimized design is initially validated by CAE methods for the hot operational conditions and worst-case circumstances. Required material properties are determined through manufactured specimens. A prototype cylinder head is manufactured using the LPBF (laser powder bed fusion) process, and hardware durability is validated on a hydro-pulse test bench under the maximum cylinder pressure of the reference Diesel engine. Subsequently, a material analysis is performed, and optimization potentials at the component geometry and printing parameters are investigated to further improve material properties and hence fatigue performance.
Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods. The first is the virtual chip test, which can track the movement of machining chips within internal cavities and tunnels of a machined part, such as the water jackets and oil galleries of a cylinder head, and the simulation results can be used to predict chip clogging locations and severity. Next, the chip clogging data are input into the second method, washer simulation, to design chip washers and washing cycles that can effectively remove the machining chips. The advantage of this methodology lies in its capability to quantify chip cleanliness risks as well as washing efficiencies with numerical quality indices, enabling comparisons of chip cleaning difficulties and evaluations of chip washer performance. The innovation of this methodology is the adaptation of a particle-based CFD method to model the behavior of machining chips as well as the dynamics of water jets in the chip washer.
When an SI engine is equipped with individual cylinder pressure transducers, combustion timing of each cylinder can be precisely controlled by adjusting spark timing in real-time. In this paper, a novel method based on principal component analysis (PCA) is introduced to control the combustion timing with a significantly less computational burden than a conventional method.
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