Browse Topic: Design processes
The first step in designing or analyzing any structure is to understand “right” set of loads. Typically, off-road vehicles have many access doors for service or getting into cab etc. Design of these doors and their latches involve a knowledge of the loads arising when the door is shut which usually involves an impact of varying magnitudes. In scenarios of these impact events, where there is sudden change of velocity within few milliseconds, produces high magnitude of loads on structures. One common way of estimating these loads using hand calculations involves evaluating the rate-of-change-of-momentum. However, this calculation needs “duration of impact”, and it is seldom known/difficult to estimate. Failing to capture duration of impact event will change load magnitudes drastically, e.g. load gets doubled if time-of-impact gets reduced from 0.2 to 0.1 seconds and subsequently fatigue life of the components in “Door-closing-event” gets reduce by ~7 times. For these problems, structures
Modern vehicle integration has become exponentially more difficult due to the complicated structure of designing wiring harnesses for multiple variants that have diverse design iterations and requirements. This paper proposes an AI-driven solution for addressing variant complexity. By using Convolutional Networks and Deep Neural Networks (CNN & DNN) to generate harness routing using defined specifications and constraints, the proposed solution uses minimal human intervention, substantially less time, and enables less complexity in designing. AI trained modelled systems can generally even predict failures in production methods which also reduces downtime and increases productivity. The new AI system automatically converts design specifications to manufacturable design specifications to avoid confusion with design parameters, by optimizing concepts with connector placements, grommet fittings, clip alignments, and other tasks. The solution coping with the inherent dynamic complexity of
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
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
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.
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
Additive manufacturing (AM) is no longer just an alternative to traditional manufacturing methods; it's a transformative shift in how parts are designed, built, and qualified. With AM, engineers can create complex internal geometries, lattice structures, and multi-functional components that simply were not possible with traditional manufacturing methods. The design freedom unlocked by AM is advantageous in the next generation of naval innovation, particularly as shipbuilding programs push to meet ambitious construction goals and improve warship readiness. For suppliers, embracing AM isn't just about swapping out tools; it's about rethinking the entire design process. Working to understand and prepare for AM-driven design and qualification changes is necessary to remain competitive in future U.S. Navy shipbuilding programs. This article will explain how new standards are driving qualification, supporting U.S. Navy construction goals and fleet readiness.
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.
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