Particle CFD for Automotive

Particle method CFD for gearboxes and engines - Because some problems cannot be answered with Finite Volume

A typical Finite Volume (FV) code won’t perform the roughly analogous remeshing operation every time step. However, there are several differences - particle methods, especially MPS, require far fewer nodes than FV, are tolerant to larger time steps, and are extremely easy to parallelize, which is not necessarily the case for FV algorithms. With the rise of parallel programming and especially scientific programming on GPU’s, this method was able to overtake FV in terms of performance for a number of problems.

How do you analyze this in Finite Volume?

If you require a case with few or no moving parts, where you have the need to resolve small features in a relatively large domain or have very complex inlet/outlet boundary conditions, you should use a FV or a Finite Element (FE) code.

If you have a complex moving geometry in an enclosure (e.g. a gearbox) or a sparsely populated domain, the advantage of the MPS method over its more established counterparts is obvious: there are no meshes, no errors introduced due to interface diffusion or scheme corrections and the run times are an order of magnitude shorter. This is not to say that MPS cannot do other problems, or that FV cannot do gearboxes – it is just that MPS is not the best choice in the first case and FV is definitely not a good choice in the second case.

What are Particle Methods for CFD?

First, particle methods for CFD are for the study of fluids, not the study of particles like sand. Particle methods study the flow of fluid using points in space 'particles' as the calculation points.

Particles can be viewed as objects carrying a physical property of the flow that is being simulated through the solution of Ordinary Differential Equations (ODE) that determine the trajectories and the evolution of the properties carried by the particles.

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Who uses Particle CFD for Automomotive?

These customers presented at the recent CAE Conference about thier use of Particleworks.

Riccardo Bergamin, ZECO
Michele Merelli, EnginSoft

Comparison between CFD and MPS Methods for Numerical Simulation of Pelton turbine

CFD modelling and validation of Pelton turbines are challenging due to the transient and multi-phase nature of the flow, that require fine and high quality grid definition, in order to accurately capture the flow features. Due to high computational time, modern CFD techniques allow to study and optimize the components of the turbine like single bucket, needle and nozzle, deviator and manifold.
Finite Volume CFD codes can be used for this kind of component simulations, but models become too complex and computationally expensive when the whole turbine and the open air casing are included in order to study jets interactions and water outflow.
Using particle-based Navier-Stokes solvers, like Particleworks and the Moving Particle Simulation method, these barriers can be overcome, with a technological breakthrough that paves the way to new study and optimization opportunities.
In this paper both Finite Volume simulations of turbine components and Moving Particle Simulation of a complete runner will be presented and comparisons with expected turbine efficiency will be shown.

Francesco Canestri, Dana Motion Systems
G. Parma, EnginSoft SpA
A. Lucchi, Dana Motion Systems
M. Galbiati, EnginSoft SpA

Churning Losses Evaluation in Swashplate Axial Piston Pump using Moving Particle Approach


In axial piston units, churning losses have a non-negligible influence on mechanical efficiency. This work presents a numerical approach for the evaluation of the churning losses in a swashplate axial piston pump for closed circuit applications using the MPS (Moving Particle Semi-implicit) software Particleworks.
Taking advantages of experimental activities and theoretical results derived by different authors [1,2,3], a sensitivity analysis is carried out in order to evaluate the influence of the numerical parameters involved in the simulation. In particular, the effects of the particle size, the slip factor applied to the wall boundaries and the turbulence model are analyzed.
In this framework, reduction of particle size clearly shows the convergence of the churning losses toward the expected value.
The paper also demonstrates that when the reduction of particle size is not affordable due to computational time and resources, the same torque results can be obtained with a coarser particle size, by increasing the slip factor, that affects the viscous forces on the walls.
The use of the turbulence model has instead a lower impact on the churning losses prediction with respect to particle size and slip factor.

Carlo Arturo De Marco, CNH Industrial
Michele Coccetta, CNH Industrial

Lubrication and Churning Losses Estimation in Gearboxes for Agricultural Equipment


Agricultural Equipment and off-road applications are always equipped with complex gears transmission to transfer the torque from the power source to the final drive or the implements, the driveline of a tractor is the most representative example of such a system. In addition, different type of gearboxes, more or less complex and compact are also used to supply torque to different places and different mechanisms of the machines, this is the case of Combines and Forage Harvesters. The simulation of the gears lubrication based on conventional CFD approach is possible by using the most recent meshing techniques developed by the main CFD software houses, however it does not seem yet so appealing from an industrial development perspective that requires tools and methodologies accurate and fast further than able to deal with many gears in the same time. In order to comply with this needs other meshless technologies (MPS in this case) have been explored and then implemented in the recent years starting from very basic test cases up to more and more complicated gear systems.

Oscar Cuevas, GIMA Transmission Technology

Gear oil jet lubrication efficiency


In off-road and in-road vehicles, new developments look forward to improve the efficiency in order to reduce the CO2 emissions. About half of the total losses come from constant losses in the whole driveline. By reducing the gear churning losses, important savings can be made by reducing oil level but for that we need to lubricate gears by oil jet. The difficulty is to determine what are the oil flow and oil jet location to lubricate and cool gear correctly according gear speed/power and design (macrogeometry). The target is to design the lubrication pipes with the lowest cost impact with good lubrication oil flow efficiency. We have analyzed one gear train in different conditions with Particlesworks to establish a rule which gives lubrication oil flow efficiency. That allows to compare oil pipes design and inlet oil flow to take decision for cost effective solution.

Nicola Pretto, MarelliMotori

Oil lubricated bearing support analysis on electric generators with mesh-less CFD methods


In multibody complex dynamic systems it is often difficult to predict oil flow path and sometimes even impossible to simulate it with traditional CFD software.
This is a very important issue in the energy industry business, that is why Marelli Motori, a designer and manufacturer of electrical motors and generators since 1891, has tested Particleworks, an innovative mesh-less software based on the moving Particle Simulation (MPS Method).
This paper analyses the oil lubricated bearing support on electric generators: using this software our engineers are able to simulate the oil flow path inside the machine and model large-scale equipment behaviour before a new product is put into production, increasing its efficiency and avoiding possible critical issues at a later stage.

David Percival, EnginSoft
Rod Giles, Royal Enfield

Optimization of the Piston cooling oil jet using Particleworks with modeFRONTIER


CFD simulations traditionally have an incredibly long computational time especially for cases involving free surface flows and moving parts with complex motion. Therefore, simulating the Piston cooling jet using traditional CFD would be impossible in a short time frame and simulation led design and design optimisation is totally unfeasible. However, by employing the MPS method with accelerated hardware, we are able to reduce the computational time to only 15 minutes and thus bring design optimization into the realms of feasibility.
This case demonstrates how we are able to modify the design of the cooling jet to optimize the cooling effect of the oil on the Piston thus improving reliability and life time of the Engine. We will also explore the techniques that were used to connect modeFRONTIER to Particleworks.


Gearbox lubrication studies with meshless CFD methods


Developing new passive lubrication systems with reduced churning losses is one of the current challenges for the automotive industry. GKN Driveline produces gearbox systems for AWD vehicles, for hybrid vehicles and for electric cars. Tight customer timings and increasing customer requirements demand tools to predict the oil flow and distribution at wide range of operating conditions already at initial development stages. The complex, moving geometries inside a gearbox lead GKN Driveline to use meshless CFD methods, e.g. SPH (smoothed particle hydrodynamics) and MPS (moving particle method) tools. These tools allow for rapid concept development and provide additional understanding of the oil flow, also in combination with experimental data. A typical gearbox study will be presented, including presentation of typical work flow and discussion of gearbox CFD specific challenges.

Designing and analysing the cooling of a medium speed engine piston using MPS method


Important constraint in designing a piston for a medium speed engine is maximum temperature of the piston. Too high piston temperature causes for example hot corrosion and decrease in material properties. When piston is developed for a new engine it is usually required that several piston geometries are tested. In early stage of the development one must be convicted that piston temperatures do not exceed general design limits. To calculate the piston temperatures thermal boundary conditions must be known. Thermal load can be determined by approximate methods or more precise combustion simulation. Determining the cooling effect of oil inside piston cooling gallery is rather difficult. Oil splashing inside piston is free surface flow which is difficult flow scenario to be simulated. Particleworks which utilizes MPS method offers an effective way to simulate oil flow and also to calculate the heat transfer coefficient. As a mesh-free method it enables quick evaluation of different designs without using long time to pre-processing. Also the actual simulation time is short compared to traditional methods. The use of MPS method and validation results are shown in the paper.

Oil path prediction and optimization for high speed transmissions with ParticleWorks


The oil flow prediction has always been a challenge for the designer. Being able to predict the path followed by the oil inside a transmission before the functional tests is not easy, especially for transmissions working in wide ranges of speed and temperature, but it would give great advantages. In particular, it would allow to shape properly the housings geometry, to define the most suitable oil level and to estimate whether the temperature can reach dangerous levels, minimizing the development costs and time and increasing the compliance with the customer requirements since the first prototypes. This is even truer when a transmission for high speeds is considered since the high speed introduces different behaviors of the oil and more attention on the oil quantity is required to minimize the power losses. A case study of a high speed transmission has been developed and simulated with ParticleWorks in order to predict the oil path at different speed levels and optimize the housing geometries to guarantee the lubrication of all the components with the lowest oil level.

HPE COXA: Particleworks application in Automotive Industry


CFD Simulation activities are every day more important in automotive industry from concept product definition to experimental validation. A Mesh-less software like Particleworks allows engineers to perform new analysis that with the standard CFD mesh based methods are not possible or even too difficult in terms of model definition and simulation time. Particleworks smart features allows a very easy model preprocessing from CAD import, to motion definition and solver setup. Another key point is the possibility to run the simulation on GPU with a considerable solution time reduction. This paper resumes HPE COXA experience using Particleworks for Transmission and Gearbox Oil Splashing, Oil Tank Sloshing and Piston Oil Jet simulation.

Case Studies on Particle CFD