Browse Topic: Product development
To facilitate the construction of a robust transport infrastructure, it is essential to implement a digital transformation of the current highway system. The concept of digital twins, which are virtual replicas of physical assets, offers a novel approach to enhancing the operational efficiency and predictive maintenance capabilities of highway networks. The present study begins with an exhaustive examination of the demand for the smart highway digital twin model, underscoring the necessity for a comprehensive framework that addresses the multifaceted aspects of digital transformation. The framework, as proposed, is composed of six integral components: spatiotemporal data acquisition and processing, multidimensional model development, model integration, application layer construction, model iteration, and model governance. Each element is critical in ensuring the fidelity and utility of the digital twin, which must accurately reflect the dynamic nature of highway systems. The
In vehicle design, the H point is a theoretical relative location measured in relation to specific characteristics that determines a group of dimensions to define vehicle interior roominess. Based on theoretical H point automakers concept their vehicle and have to make important decisions on vehicle architectural that could result in a bad product for the future customers and during the early phase of vehicle development, one of the key design attributes to consider is in relation to the interior comfort of the user, so that its design and its components enabling a favorable interaction with the occupant. Vehicle interior roominess is one of the key factors for buyers’ satisfaction with certain features such as the shoulder room, headroom and couple distance, among others, may influence the level of satisfaction of the occupants’ comfort. One of these items refers to the rear chair height (H30-2), which is presented while by the distance of rear H-point to the vehicle floor affecting
During the early phase of vehicle development, one of the key design attributes to consider is the trunk. Trunk is the pillar that is responsible for user’s accommodate their baggage and make into customer needs in engineer metrics. Therefore, it is one of the key requirements to be considered during the vehicle design. Certain internal vehicle trunk characteristics such as the trunk height and length are engineer metrics that influence the occupants’ perception for trunk. One specific characteristic influencing satisfaction is the rear opening width lower for notch back segment, which is the subject of this paper. The objective of this project is to analyze the relationship between the rear opening width lower with the occupant’s satisfaction under real world driving conditions, based on research, statistical data analysis and dynamic clinics.
Systems Engineering is a method for developing complex products, aiming to improve cost and time estimates and ensure product validation against its requirements. This is crucial to meet customer needs and maintain competitiveness in the market. Systems Engineering activities include requirements, configuration, interface, deadlines, and technical risks management, as well as definition and decomposition of requirements, implementation, integration, and verification and validation testing. The use of digital tools in Systems Engineering activities is called Model-Based Systems Engineering (MBSE). The MBSE approach helps engineers manage system complexity, ensuring project information consistency, facilitating traceability and integration of elements throughout the product lifecycle. Its benefits include improved communication, traceability, information consistency, and complexity management. Major companies like Boeing already benefit from this approach, reducing their product
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
Recent advancements in electric vertical take-off and landing (eVTOL) aircraft and the broader advanced air mobility (AAM) movement have generated significant interest within and beyond the traditional aviation industry. Many new applications have been identified and are under development, with considerable potential for market growth and exciting potential. However, talent resources are the most critical parameters to make or break the AAM vision, and significantly more talent is needed than the traditional aviation industry is able to currently generate. One possible solution—leverage rapid advancements of artificial intelligence (AI) technology and the gaming industry to help attract, identify, educate, and encourage current and future generations to engage in various aspects of the AAM industry. Beyond Aviation: Embedded Gaming, Artificial Intelligence, Training, and Recruitment for the Advanced Air Mobility Industry discusses how the modern gaming population of 3.3 million
Emergence of Software Defined Vehicles (SDVs) presents a paradigm shift in the automotive domain. In this paper, we explore the application of Model-Based Systems Engineering (MBSE) for comprehensive system simulation within the SDV architecture. The key challenge for developing a system model for SDV using traditional methods is the document centric approach combined with the complexity of SDV. This MBSE approach can help to reduce the complexity involved in Software-Defined Vehicle Architecture making it more flexible, consistent, and scalable. The proposed approach facilitates the definition and analysis of functional, logical, and physical architecture enabling efficient feature and resource allocation and verification of system behaviour. It also enables iterative component analysis based on performance parameters and component interaction analysis (using sequence diagrams).
With the trend of increasing technological complexity, software content and mechatronic implementation, there are increasing risks from systematic failures and random hardware failures, which is to be considered within the scope of functional safety. ISO 26262 series of standards provides guidance to mitigate these risks by providing appropriate requirements and processes. To develop a safe product with respect to above mentioned complexities, it is very critical to develop a safe system and hence a thorough and robust “Technical Safety Concept” is very important to ensure absence of unreasonable risk due to hazards caused by malfunctions of E/E systems. ISO26262-Part 4 provides guidelines for “Product development at the system level”, to design safety-related systems that include one or more electrical and/or electronic (E/E) systems and that are installed in series production road vehicles. Defining requirements at system level for each individual technology and systematically
Today's battery management systems include cloud-based predictive analytics technologies. When the first data is sent to the cloud, battery digital twin models begin to run. This allows for the prediction of critical parameters such as state of charge (SOC), state of health (SOH), remaining useful life (RUL), and the possibility of thermal runaway events. The battery and the automobile are dynamic systems that must be monitored in real time. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. Because automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud. As a result, the inherent lag in data transfer between the cloud and cars challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes applying a thermal runaway model on edge devices as a strategy to reduce
Agile software development aims to create high-quality products while minimizing waste, reducing project costs. Nevertheless, costs are not decreasing despite shorter project cycles and more compact, flexible teams. One area where consideration is being given to reevaluating the stages in software product development is RT. Regression testing is a form of testing done to assure that changes done in Model do not adversely affect the software's functionality. As software develops, test suites typically expand and may become too expensive to run through in their entirety The initial application might have good set of test cases, and running the entire test suite could make testing more expensive. Three ways for reducing the cost of RT include test instance prioritization, test suite minimizing, and regression test selection. In order to verify that software satisfies customer requirements, identify faults or bugs in the code, and determine how to fix these issues to make the software more
Researchers at the Johns Hopkins Applied Physics Laboratory have developed a machine learning method that could have a huge impact on understanding how material is formed during the additive manufacturing process. John Hopkins Applied Physics Laboratory, Laurel, MD Researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, have demonstrated a novel approach for applying machine learning to predict microstructures produced by a widely used additive manufacturing technique. Their approach promises to dramatically reduce the time and cost of developing materials with tailored physical properties and will soon be implemented on a NASA-funded effort focused on creation of a digital twin. “We anticipate that this new approach will be extremely impactful in helping design and understand material formation during additive manufacturing processes, and this fits into our overarching strategy focused on accelerating materials development for national security,” said
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