Browse Topic: Product development
Automotive chassis components are considered as safety critical components and must meet the durability and strength requirements of customer usage. The cases such as the vehicle driving through a pothole or sliding into a curb make the design (mass efficient chassis components) challenging in terms of the physical testing and virtual simulation. Due to the cost and short vehicle development time requirement, it is impractical to conduct physical tests during the early stages of development. Therefore, virtual simulation plays the critical role in the vehicle development process. This paper focuses on virtual co-simulation of vehicle chassis components. Traditional virtual simulation of the chassis components is performed by applying the loads that are recovered from multi-body simulation (MBD) to the Finite Element (FE) models at some of the attachment locations and then apply constraints at other selected attachment locations. In this approach, the chassis components are assessed
Model-Based Systems Engineering (MBSE) enables requirements, design, analysis, verification, and validation associated with the development of complex systems. Obtaining data for such systems is dependent on multiple stakeholders and has issues related to communication, data loss, accuracy, and traceability which results in time delays. This paper presents the development of a new process for requirement verification by connecting System Architecture Model (SAM) with multi-fidelity, multi-disciplinary analytical models. Stakeholders can explore design alternatives at a conceptual stage, validate performance, refine system models, and take better informed decisions. The use-case of connecting system requirements to engineering analysis is implemented through ANSYS ModelCenter which integrates MBSE tool CAMEO with simulation tools Motor-CAD and Twin Builder. This automated workflow translates requirements to engineering simulations, captures output and performs validations. System
E-mobility is revolutionizing the automotive industry by improving energy-efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy-efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under
In the automotive industry, there have been many efforts of late in using Machine Learning tools to aid crash virtual simulations and further decrease product development time and cost. As the simulation world grapples with how best to incorporate ML techniques, two main challenges are evident. There is the risk of giving flawed recommendations to the design engineer if the training data has some suspect data. In addition, the complexity of porting simulation data back and forth to a Machine Learning software can make the process cumbersome for the average CAE engineer to set up and execute a ML project. We would like to put forth a ML workflow/platform that a typical CAE engineer can use to create training data, train a PINN (Physics Informed Neural Network) ML model and use it to predict, optimize and even synthesize for any given crash problem. The key enabler is the use of an industry first data structure named mwplot that can store diverse types of training data - scalars, vectors
Physical testing is required to assess multiple vehicles in different conditions, specially to validate those related to regulations. The acoustic evaluations have difficulties and limitations in physical test; cost and time represent important considerations every time. Additionally, the physical validation happens once a prototype has been built, this takes place in a later phase of the development. Sound pressure is measured to validate different requirements in a vehicle, horn sound is one of these and it is related to a regulation of united nations (ECE28). Currently the validation happens in physical test only and the results vary depending on the location of the horn inside the front end of every vehicle. [7] In this article, the work for approaching a virtual validation method through CAE is presented with the intention to get efficiency earlier in product development process.
The vehicle wake region is of high importance when analyzing the aerodynamic performance of a vehicle. It is characterized by turbulent separated flow and large low-pressure regions that contribute significantly to drag. In some cases, the wake region can oscillate between different modes which can pose an engineering challenge during vehicle development. Vehicles that exhibit bimodal wake behavior need to have their drag values recorded over a sufficient time period to take into account the low frequency shift in drag signal, therefore, simulating such vehicle configurations in CFD could consume substantial CPU hours resulting in an expensive and inefficient vehicle design iterations process. As an alternative approach to running simulations for long periods of time, the impact of adding artificial turbulence to the inlet on wake behavior and its potential impact on reduced runtime for design process is investigated in this study. By adding turbulence to the upstream flow, the wake
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
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
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.
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
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
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
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