Browse Topic: Design processes
Thermal Management System (TMS) for Battery Electric Vehicles (BEV) incorporates maintaining optimum temperature for cabin, battery and e-powertrain subsystems under different charging and discharging conditions at various ambient temperatures. Current methods of thermal management are inefficient, complex and lead to wastage of energy and battery capacity loss due to inability of energy transfer between subsystems. In this paper, the energy consumption of an electric vehicle's thermal management system is reduced by a novel approach for integration of various subsystems. Integrated Thermal Management System (ITMS) integrates air conditioning system, battery thermal management and e-powertrain system. Characteristics of existing integration strategies are studied, compared, and classified based on their energy efficiency for different operating conditions. A new integrated system is proposed with a heat pump system for cabin and waste heat recovery from e-powertrain. Various cooling
In both internal combustion engine (ICE) and electric vehicles, Heating, Ventilation, and Air Conditioning (HVAC) systems have become significant contributors to in-cabin noise. Although significant efforts have been made across the industry to reduce noise from airflow handling systems, especially blower noise. Nowadays, original equipment manufacture’s (OEMs) are increasingly focusing on mitigating noise generated by refrigeration handling systems. Since the integration of refrigeration components is vital for the overall Noise Vibrations and Harshness (NVH) refinement of a vehicle, analysing the impact of each HVAC component during vehicle-level integration is essential. This study focused on optimizing the NVH performance of key refrigeration components, including the AC compressor, thermal expansion valve (TXV), suction pipe, and discharge line. The research began with a theoretical investigation of the primary noise and vibration sources, particularly the compressor and TXV
This research is dedicated to exploring the application of large language models in the Beijing Subway scientific research project management platform. It conducts a thorough analysis of many key elements, including the application background, technical support, practical achievements, and future development paths. With the continuous development of the Beijing Subway construction scale, the number and complexity of scientific research projects have been gradually increasing. Traditional management models are getting more and more insufficient in dealing large amounts of data, complicated processes, and precise decision-making requirements. By using natural language processing, machine learning, knowledge graph pedigreestechnological and technical model related technologies, which are very different from the one of the most inventive ones, are presented. The objective of intelligence is to solve this model by automatically analyzing papers with a logical and scientific approach and
The Ground Vehicle Systems Center (GVSC) has an ongoing effort to use Industrial Design to explore the toughest problems faced by the Army modernization community. That effort takes several steps from the Design thinking discipline and seeks to understand Soldier perspectives, define problems and propose conceptual solutions. This paper summarizes the employment of Industrial Design at GVSC as well as outputs from two key Design projects. It concludes by presenting the combined learned outcomes from several Design efforts at GVSC and proposes ways in which Industrial Design and Design Thinking can better drive Army modernization, by understanding user’s needs, and committing to Innovation.
Ground vehicle software continues to increase in cost and complexity, in part driven by tightly integrated systems and vendor lock-in. One method of reducing costs is reuse and portability, encouraged by the Modular Open Systems Approach and the Future Airborne Capability Environment (FACE) architecture. While FACE provides a Conformance Testing Suite to ensure portability between compliant systems, it does not verify that components correctly implement standard interfaces and desired functionality. This paper presents a layered test methodology designed to ensure that a FACE component correctly implements working communication interfaces, correctly handles the full range of data the component is expected to manage, and correctly performs all of the functionality the component is required to perform. This testing methodology includes unit testing of individual components, integration testing across multiple units, and full hardware in the loop system integration testing, offering a
This paper presents a model-based systems engineering (MBSE) and digital twin approach for a military 6T battery tester. A digital twin architecture (encompassing product, process, and equipment twins) is integrated with AI-driven analytics to enhance battery defect detection, provide predictive diagnostics, and improve testing efficiency. The 6T battery tester’s MBSE design employs comprehensive SysML models to ensure traceability and robust system integration. Initial key contributions include early identification of battery faults via impedance-based sensing and machine learning, real-time state-of-health tracking through a synchronized virtual battery model, and streamlined test automation. Results indicate the proposed MBSE/digital twin solution can detect degradation indicators (e.g. capacity fade, rising internal impedance) earlier than traditional methods, enabling proactive maintenance and improved operational readiness. This approach offers a reliable, efficient testing
A design is presented for an electro-mechanical switchgear, intended for reconfiguring the windings of an electric machine whilst in operation. Specifically, the design is developed for integration onto an in-wheel automotive motor. The motor features 6 phase fractions, which can be reconfigured by the switchgear between series-star or parallel-star arrangements, thereby doubling the torque or speed range of the electric machine. The switchgear has a mass of only 1.8kg – around one tenth of the equivalent 2-speed transmission which might otherwise be employed to achieve a similar effect. As well as the extended operating envelope, the reconfigurable winding motor offers benefits in efficiency and power density. The mechanical solution presented is expected to achieve efficiency and cost advantages over equivalent semiconductor-based solutions, which are practical barriers to adoption in automotive applications. The design uses only mechanical contacts and a single actuator, thereby
The multinational EPIIC programme, involving Airbus Defence and Space, is exploring multiple exciting innovations to strengthen Europe's defense capabilities and technological sovereignty. Airbus, Toulouse, France Imagine Tony Stark soaring through the skies in his iconic Iron Man suit, each command answered with a seamless blend of futuristic technology. Now imagine the cockpit of tomorrow's fighter jet.
Imagine being handed a device that’s meant to help you — but instead feels intimidating, confusing, or painful to use. For millions of patients around the world, that’s the reality of managing treatment at home. Across ailments, the burden of self-administered care is growing, and with it, the importance of designing drug-delivery systems designed with the patient experience at their core.
How Cummins used modeling and other advanced design software to create its most efficient engines yet. As AI and other deep-learning tools begin to help shape the transportation industry, they also bring improvements to existing technology. Modeling and simulation software has rapidly become a crucial tool for improving the design process of new diesel engines. More than two decades after the first X15 engines rolled off the assembly line, Cummins has applied today's modeling tools to help create the HELM version of the X15. The HELM architecture (which stands for Higher Efficiency, Lower emissions and Multiple fuels) is the company's basis for a global platform capable of meeting all manners of emissions regulations while still serving customers across a wide variety of use cases.
Rolling bearings with optimized friction and performance characteristics can have a significant influence on reducing the power loss, design envelope and weight of hydraulic motors and pumps, gearboxes and axles in construction machinery. If correctly designed, rolling bearings can make a significant contribution to reducing carbon dioxide emissions. Most construction machinery is still operated conventionally, using diesel engines and hydraulic components. In the widely used adjustable axial piston pumps and motors, the input and output shaft are usually supported by two tapered roller bearings that are adjusted against each other. When designing the bearing support, it is advisable to reduce the preload to precisely the required minimum allowed by the load spectrum. The lower bearing preload leads to permanently lower axial forces between the tapered roller end face and inner ring rib and, therefore, to a corresponding reduction in frictional torque.
The advent of EVs, ride sharing, global events such as the pandemic, chip shortage, and increasing dependency on suppliers are just some factors reshaping the automotive business. Consumer sentiment moving from product to experience resulted in more variants being launched at a record pace. Consequently, product development processes need to be more agile and yet more rigorous while bringing about cohesion and alignment across cross-functional teams to launch vehicles on time, on quality, and in budget. Automotive companies have been using Product Lifecycle Management (PLM) solutions for years to manage CAD, change, and BOMs. With changing business scenarios and increasing complexity of products, the sphere of influence of PLM solutions has expanded significantly over the last decade to manage all aspects of product development. Traditionally PLM software focused on integrating with different authoring tools and managing data in a central repository. The PLM solution had multiple such
The design, development, and optimization of modern suspension systems is a complex process that encompasses several different engineering domains and disciplines such as vehicle dynamics simulation, tire data analysis, 1D lap-time simulation, 3D CAD design and structural analysis including full 3D collision detection. Typically, overall vehicle design and suspension development are carried out in multiple iterative design loops by several human specialists from diverse engineering departments. Fully automating this iterative design process can minimize manual effort, eliminate routine tasks and human errors, and significantly reduce design time. This desired level of automation can be achieved through digital modeling, automated model generation, and simulation using graph-based design languages and an associated language compiler for translation and execution. Graph-based design languages ensure the digital consistency of data, the digital continuity of processes, and the digital
Engineering precision is an art of nuance — especially when it comes to selecting the right bearing for medical devices. What begins as a straightforward specification process quickly becomes a complex yet familiar puzzle of competing requirements. Oftentimes, engineers discover that a bearing’s performance extends beyond its basic dimensional specs, involving considerations of material properties, system integration and supply chain dynamics.
This SAE Aerospace Standard (AS) provides design criteria for onboard stairways intended for use by passengers aboard multi-deck transport category airplanes. It is not intended for stairways designed for use only by crewmembers, supernumeries, or maintenance personnel. Additionally, this AS does not apply to fuselage mounted or external stairways used for boarding passengers, which are covered by ARP836.
Letter from the Guest Editors
A good Noise, Vibration, and Harshness (NVH) environment in a vehicle plays an important role in attracting a large customer base in the automotive market. Hence, NVH has been given significant priority while considering automotive design. NVH performance is monitored using simulations early during the design phase and testing in later prototype stages in the automotive industry. Meeting NVH performance targets possesses a greater risk related to design modifications in addition to the cost and time associated with the development process. Hence, a more enhanced and matured design process involves Design Point Analysis (DPA), which is essentially a decision-making process in which analytical tools derived from basic sciences, mathematics, statistics, and engineering fundamentals are used to develop a product model that better fulfills the predefined requirement. This paper shows the systematic approach of conducting a Design Point Analysis-level NVH study to evaluate the acoustic
Electrification in the automotive industry has been steadily rising in popularity for many years, and with any technology there is always a desire to reduce development cost by efficiently iterating designs using accurate simulation models. In the case of rotating machinery and other devices that produce vibrations, an important physical behavior to simulate is Noise Vibration and Harshness (NVH). Efficient workflow to account for NVH was established at Schaeffler for eMotor design. Quantitative prediction is difficult to achieve and is occasionally intended only for faster iterations and trend prediction. A good validated qualitative simulation model would help achieve early NVH risk assessment based on the specified requirement and provide design direction and feasibility guidance across the design process to mitigate NVH concerns. This paper seeks to provide a general approach to validate the simulation model. The correlation methods used in this paper consist of a combination of
High-frequency whine noise in electric vehicles (EVs) is a significant issue that impacts customer perception and alters their overall view of the vehicle. This undesirable acoustic environment arises from the interaction between motor polar resonance and the resonance of the engine mount rubber. To address this challenge, the proposal introduces an innovative approach to predicting and tuning the frequency response by precisely adjusting the shape of rubber flaps, specifically their length and width. The approach includes the cumulation of two solutions: a precise adjustment of rubber flap dimensions and the integration of ML. The ML model is trained on historical data, derived from a mixture of physical testing conducted over the years and CAE simulations, to predict the effects of different flap dimensions on frequency response, providing a data-driven basis for optimization. This predictive capability is further enhanced by a Python program that automates the optimization of flap
Every vehicle has to be certified by the concerned governing authority that it matches certain specified criteria laid out by the government for all vehicles made or imported into that country. Horn is one of the components that is tested for its function and sound level before a vehicle is approved for production and sale. Horn, which is an audible warning device, is used to warn others about the vehicle’s approach or presence or to call attention to some hazard. The vehicle horn must comply with the ECE-R28 regulation [1] in the European market. Digital simulation of the horn is performed to validate the ECE-R28 regulation. In order to perform this, a finite element model of a cut model of a vehicle, which includes the horns and other components, is created. Fluid-structure coupled numerical estimation of the sound pressure level of the horn, with the appropriate boundary conditions, is performed at the desired location as per the ECE-R28 regulation. The simulation results thus
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