Browse Topic: Cost analysis
Zero emission vehicles are essential for achieving sustainable and clean transportation. Hybrid vehicles such as Fuel Cell Electric Vehicles (FCEVs) use multiple energy sources like batteries and fuel cell stacks to offer extended driving range without emitting greenhouse gases. Optimal performance and extended life of the important components like the high voltage battery and fuel-cell stack go a long way in achieving cost benefits as well as environmental safety. For this, energy management in FCEVs, particularly thermal management, is crucial for maintaining the temperature of these components within their specified range. The fuel cell stack generates a significant amount of waste heat, which needs to be dissipated to maintain optimal performance and prevent degradation, whereas the battery system needs to be operated within an optimal temperature range for its better performance and longevity. Overheating of batteries can lead to reduced efficiency and potential safety hazards, while low temperatures can decrease battery performance and range. The multiple temperature control loops in the thermal system design of the current FCEVs require significant energy for continuous heating and cooling. This is due to the fact that each of them exchanges energy directly with an external source or sink without redistributing energy among themselves. This can lead to energy losses during the heat exchange process. Our goal is to optimize thermal energy usage while maintaining the same performance and efficiency of both battery electric system and the fuel cell stack in a vehicle. In this paper, an analysis of thermal energy utilization of a single system is compared to the exchange of thermal energy across multiple systems, considering various heating and cooling scenarios. We compare our proposed strategy (with redistribution) with the existing strategy (without redistribution) quantitatively with respect to controller effort/ energy spent in achieving thermal target.
The emergence of electric Vertical Takeoff and Landing (eVTOL) air vehicles is transforming how people and freight are moved in short distances. This transformation has a profound impact on surrounding infrastructure necessary to provide Aircraft On Ground support for eVTOLs. The hover capabilities of eVTOLs have similar operating characteristics within terminal and uncontrolled airspace. However, the need to conserve battery energy via rapid approaches and departures affects terminal airspace management. To attract eVTOL operators, existing airports, landing zones, and vertiports are modifying their infrastructure to include fixed electric charging stations, additional taxiways, upgraded fire suppression systems, separate hangers, and capable MRO facilities. Augusta Regional Airport (KAGS) is the base airport for the annual Masters Golf Tournament which experiences five times the normal airport traffic and some 40,000 commuting patrons. eVTOLs can offset land traffic issues associated with commuters and supplies. Since KAGS is centroid to 32,000 square miles of territory void of major highways, basing eVTOLs can offer expedited transit services for people and goods which will have a profound impact on the economic viability and quality of life in the area.
This research explores the use of salt gradient solar ponds (SGSPs) as an environmentally friendly and efficient method for thermal energy storage. The study focuses on the design, construction, and performance evaluation of SGSP systems integrated with reflectors, comparing their effectiveness against conventional SGSP setups without reflectors. Both experimental and numerical methods are employed to thoroughly assess the thermal behavior and energy efficiency of these systems. The findings reveal that the SGSP with reflectors (SGSP-R) achieves significantly higher temperatures across all three zones—Upper Convective Zone (UCZ), Non-Convective Zone (NCZ), and Lower Convective Zone (LCZ)—with recorded temperatures of 40.56°C, 54.2°C, and 63.1°C, respectively. These values represent an increase of 6.33%, 11.12%, and 14.26% over the temperatures observed in the conventional SGSP (SGSP-C). Furthermore, the energy efficiency improvements in the UCZ, NCZ, and LCZ for the SGSP-R are considerable, showing increases of 39.18%, 35.46%, and 39.64%, respectively, when compared to the SGSP-C. The numerical simulations are in strong agreement with the experimental results, exhibiting minimal deviations of less than 5% in both temperature distribution and energy efficiency across all zones. This study underscores the potential of SGSPs with reflectors for enhanced thermal storage performance.
Soft skin coverings and touch sensors have emerged as a promising feature for robots that are both safer and more intuitive for human interaction, but they are expensive and difficult to make. A recent study demonstrates that soft skin pads doubling as sensors made from thermoplastic urethane can be efficiently manufactured using 3D printers.
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also significant to the success of cost reduction strategies. Brand reputation and customer perceptions of quality must be safeguarded when changes are implemented. To that end, communication strategies to convey the benefits of cost reduction without compromising perceived value are a key factor to enhance market acceptance. Another crucial element in the execution of cost reduction projects is operational efficiency. Streamlining production processes, optimizing supply chain logistics, and embracing automation technologies require careful planning and implementation to avoid disruptions in production schedules. In conclusion, addressing the challenges of reducing costs in automotive body exterior parts demands a holistic approach that considers financial, functional, and marketing aspects. Striking the right balance between these elements is essential for the success of cost reduction initiatives, ensuring that the automotive industry remains competitive while meeting the demands of a cost-conscious market. A solid technical background for all the parties involved is imperative, and this text provides an overview of the pivotal topics in that context.
North American automakers and EV battery firms have five years to erase China's dominance in technology and manufacturing or they may face the reality of buying batteries from China for the foreseeable future. That was the message from battery-analysis company Voltaiq CEO Tal Sholklapper at a media briefing in Detroit. “We're in the final innings now,” Sholklapper said. “If the industry around batteries and electric vehicles and all the follow-on applications wants to make it, we're going to have to change the way we play.”
The future of wireless technology - from charging devices to boosting communication signals - relies on the antennas that transmit electromagnetic waves becoming increasingly versatile, durable and easy to manufacture. Researchers at Drexel University and the University of British Columbia believe kirigami, the ancient Japanese art of cutting and folding paper to create intricate three-dimensional designs, could provide a model for manufacturing the next generation of antennas. Recently published in the journal Nature Communications, research from the Drexel-UBC team showed how kirigami - a variation of origami - can transform a single sheet of acetate coated with conductive MXene ink into a flexible 3D microwave antenna whose transmission frequency can be adjusted simply by pulling or squeezing to slightly shift its shape.
This study investigates the use of machine learning (ML) models to estimate the gross weight (GW), the longitudinal position of the center of gravity (CGx), and 1/rev cyclic flapping angles (Δ1c and Δ1s) of a compound helicopter with three redundant controls - main rotor RPM, collective propeller thrust, and stabilator angle. Neural Network (NN), Gaussian Process for Regression (GPR), and Support Vector Machine (SVM) algorithms are employed to develop estimation models using supervised training. The airspeed, redundant controls, main rotor controls, aircraft attitudes, and main rotor torque are selected as input variables (predictors) to the models due to their accessibility through the aircraft Health and Usage Monitoring System (HUMS). The dataset is split into low-speed and high-speed regimes to compare the prediction accuracy and training cost of separate regime models against a combined full-regime model. Separate airspeed regime GPR models showed superior performance in GW estimation, with higher accuracy and cost-effectiveness compared to a single full-regime model. For CG estimation, GPR again outperformed NN and SVM, although the maximum outlier errors increase significantly if a 95% confidence interval is considered. Finally, for 1/rev cyclic flapping angle predictions, SVM estimations, though not superior to GPR or NN, were acceptable and had a significantly lower computational cost. The study also examined the importance of predictors, highlighting that, on average, certain predictors like rotor RPM and rotor torque are less influential, but their removal degraded performance and had no cost benefit.
Vehicle quality and affordability will always be the most distinguishing summative characteristics in a fully saturated and highly competitive market. While vehicle quality differentiates between brands in any market segment, affordability remains the key decisive factor for many buyers in each segment. Equally important, affordability is a critical factor in achieving equity in transportation by providing reasonably priced vehicles with quality fitting the needs of different users. Keeping in mind that the cost of quality is usually in conflict with affordability, the main challenge during the different phases of the vehicle design and development process from inception to production becomes the achievement of the multi-objective conflicting goals of maximizing affordability and quality at the same time. In this paper, guided by quality characteristics framework, that accounts for affordability as a context and structured participation of the customers during the vehicle realization process, the maximization of quality achievements within the preestablished affordability targets throughout the process is studied and discussed. By establishing and monitoring affordability and quality targets by the quality management system along with integrating customers’ participations at critical phases during the realization process from inception to production, the necessary inputs for decision making to deconflict the multi-objective goals of maximizing quality and affordability throughout the product design and development process could be achieved. To ensure customer satisfaction for quality and stay within targeted affordability, changes to the quality management system and product development process traditional customer participation are proposed. These changes are necessary to integrate affordability as the quality context in the traditional quality management system and include systematic customers’ participation at the end of selected key stages of the vehicle realization. By adding customers’ reviews at critical phases during the realization process, the needed customers’ inputs to achieve the desired vehicle quality within the established tolerances and affordability targets could be achieved.
Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods. The first is the virtual chip test, which can track the movement of machining chips within internal cavities and tunnels of a machined part, such as the water jackets and oil galleries of a cylinder head, and the simulation results can be used to predict chip clogging locations and severity. Next, the chip clogging data are input into the second method, washer simulation, to design chip washers and washing cycles that can effectively remove the machining chips. The advantage of this methodology lies in its capability to quantify chip cleanliness risks as well as washing efficiencies with numerical quality indices, enabling comparisons of chip cleaning difficulties and evaluations of chip washer performance. The innovation of this methodology is the adaptation of a particle-based CFD method to model the behavior of machining chips as well as the dynamics of water jets in the chip washer.
The demand for electric vehicles (EVs) has been steadily increasing in recent years, led by the factors like environmental concerns, government incentives, and improvements in EV technology. The EV’s growth is expected to increase in the coming years as EVs become more affordable and more models become available on the market. Predicting the price of electric vehicles provides valuable insights on the EV market and inform a range of business, consumer, financial, and policy decisions. Predicting the price of electric vehicles using simple linear regression involves building a linear regression model with a single independent variable usually the vehicle’s characteristics or features to predict the dependent variable the price.This work has predicted the price of Electric Vehicle using a data set prepared for the Indian context. It has been predicted that there is significant correlation between battery capacity in Ah and the vehicle price. The measured RMSE value is 26274.942642891292. The measured value indicates that the model is better at predicting the price of an electrical vehicle.
Medical and surgical instruments are utilized daily to save and improve lives. Because of this, they demand an exact level of accuracy and infallibility in their manufacture. Traditionally, aluminum and other metals have been the standard material of choice for medical and surgical instruments due to their weight, strength, durability, and cost benefits. However, new advances in technology are challenging the status quo and offering exciting new manufacturing possibilities that allow for greater material choices. One such advancement already making waves in the aerospace, leisure, and automotive industries — and poised to benefit medical and surgical manufacturing — is Additive Fusion Technology (AFT)™.
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