Thermal Analysis of Electrical Equipment A review and comparison of different methods

Heavy equipment manufacturers want to design products that are durable and perform at their peak under a variety of conditions. To accomplish this, Altair provides an integrated multi-disciplinary simulation environment to virtually test and optimize equipment performance and therefore, help reduce design and development costs. Using simulation-driven design, studying the full dynamics of a product or system is possible, from motion analysis to complete lifecycle durability testing.

A key development goal of any machine-building project is to produce perfectly running, reliable machines that make high-quality products. By leveraging accurate virtual prototypes, seamless production can be ensured earlier in the development process to help assess and improve product profitability.

Heavy mobile machines consist mostly of production equipment working almost twenty hours a day, year on year, in diverse harsh environments, undergoing extreme loads and overloads. Especially diggers and loaders such as hydraulic excavators, wheel loaders, and backhoes, cater to multiple applications with use cases such as digging, trenching, loading, lifting, breaking, and ripping. Many times, these machines undergo non-standard uses where the machine is subjected to unplanned forces and moments as in the case of self-loading on a trailer, or a bucket hitting a dump truck body. This paper highlights the workflow process and simulation-driven methods to integrate multi-physics with Altair’s industry-leading solutions. The latest generation of Altair simulation tools can capture a wider range of vehicle systems and environmental interactions.

Information silos present a major challenge to Heavy Equipment OEMs. Poor integration of simulation models across the product life cycle, limited reuse of models between programs, and a variation of modeling maturity across various engineering disciplines result in lack of traceability and ultimately hampers development efficiency and product performance. Using system modeling and asset-centric data analytics solutions help develop and orchestrate coherent models to increase decision-making confidence and speed.

Learn how Altair AcuSolve™ performs with AMD EPYC™ 7003 series processors

Fluid mechanics simulation is a critical tool for late-stage failure risk mitigation, as well as a driver of design insights throughout the product development process. Used across all levels of product design and validation, from design engineers seeking to understand fluid and thermal effects on a design proposal to analysts performing advanced aerodynamic modeling, Computational Fluid Dynamics (CFD) serves a broad array of applications and a range of users with varied levels of expertise. The sometimes complex and computationally intensive nature of CFD necessitates careful consideration of the software and hardware investments required to produce accurate solutions and scale them at the speed of a company’s development process.

As of today, the “classical” V diagram is very well known among more and more engineers. Nonetheless its usage – even partly – is far away from the potential that it offers. One reason might be, that its benefits are not really obvious for the end-users. With this presentation, we will bring a new view by “closing the old V” and transferring it to a “closed ∇ (Nabla) cycle”. The focus of this contribution is on the opportunities to significantly increase the effectiveness of the approach of model-based development (MBD) by re-using engineering efforts in multiple ways.

Reducing aircraft design and development time is critical for all aircraft manufacturers, from urban air mobility and electric aircraft startups to military to commercial OEMs. In order to fully understand and optimize the complex systems of systems required in modern aircraft, aerospace engineers leverage a simulation method called Model-based Systems Engineering (MBSE). MBSE allows the evaluation of various types of vehicle systems to determine which best meet the mission requirements.

In this article, appearing in the Fall 2020 issue of Engine + Powertrain Technology International, Altair outlines how a holistic approach to propulsion system design is enabling manufacturers to meet performance requirements while maximizing vehicle range.

Simulation helps you validate at the end of a product design cycle, but deployed early and throughout a development process, it can actually allow you to explore more potential solutions, collaborate more effectively and optimize the design for cost, performance, weight, and other important criteria. This infographic provides a framework for developing and implementing your own simulation-driven process to help you produce more efficient e-motors and shorten development times. 

High accuracy sensors and encoders are integral components of an e-motor drive, greatly impacting the quality and efficiency on the system. A purpose-driven simulation approach is needed to account for all the physical interdependencies within these complex multi-domain systems.

Today, most products are complex mechatronic combinations of advanced technologies, mixing electrical parts with controllers and embedded software. To efficiently manage innovative products, organizations are turning to a Model-Based Development approach for concept studies, control design, multi-domain system simulation and optimization. To meet this demand, Altair’s simulation and optimization suite aims to transform design and decision-making throughout product lifecycles with their multi-disciplinary software tools and consultancy services.

A company specializing in 3D printing relies on simulation to make tools for injection molding that are less expensive, lighter and better than those created with traditional methods.

To design and build an aerial ladder for a firetruck, the engineer needs to accurately determine the working loads the ladder will encounter. Some of these can be easy to interpret such as the weight of the firefighter in the basket at the end of the ladder, or the weight of the water being supplied to the nozzle. Other loads can be a little harder to quantify, such as how wind affects the ladder. There are several different ways to determine this effect, and two of those will be explored in this paper: the standard equation (ASCE 7-10), and CFD.

Optimal design methods involving the coupling of fluid and structural solutions are a topic of active research; particularly for aerospace applications. The paper presents a coupled fluid and structure approach to topology optimization using two commercial finite element solutions; AcuSolve and OptiStruct. A gradient based method is used to minimize the compliance of a structure subject to thermal loading. The optimal material distribution to minimize compliance is computed using the Solid-Isotropic Material with Penalty (SIMP) method available in OptiStruct. A volume fraction constraint is imposed in order to iteratively reduce the parts mass. Draw constraints are used to ensure manufacturability. The thermal loading is computed iteratively using a computational fluid dynamics (CFD) solution from AcuSolve. The optimization produces an innovative design which increases the heat rejection rate of the part while reducing the mass.

XLDyn® allows the product engineer to develop and track requirements associated with different verification methods, so the current project status is always available. In addition, XLDyn® has fully integrated system level Design of Experiments (DoE) that provides valuable design guidance to select the best set of parameters or parts. Even test data can be included in the DoE.

This article mainly focusses on the electrical engineering aspects of the design. Hydrogenerators parameters extraction and dynamical behavior prediction can be easily determined with a two-dimensional finite element modeling.

Development tools and methods, such as simulation, are increasingly important to face and address the pressure of innovation. As an example, for successful new design methods and to show how simulation tools are used, Altair developed a virtual demonstrator based on a cobot application. This complex machine interacts with a human operator as the ultimate smart manufacturing equipment - to show how challenges in modern product design can be overcome.

When applied to engineering, Machine Learning can be a powerful tool to aid in a range of applications, from faster finite-element (FE) model building to optimizing manufacturing processes and obtaining more accurate results from physics-based simulations. Although incorporating this collection of technology is relatively new in the field of engineering, Altair has made leaps forward in this space to provide users with the tools they need to make a difference.

When developing mobile machines, manufacturer focus is twofold: 1) Increasing a machine’s productivity and operator comfort 2) Improving its energy efficiency. To achieve these objectives, it is crucial to have an optimized system-of-systems and seamless interaction between subsystems. But how can manufacturers design components from varied disciplines like mechanics, electronics, and hydraulics to create a holistic overall system having optimal performance? The answer is digital transformation.