Article
Engineering, Mechanical
Cheng Wang
Summary: Gear modification is an effective technology to address vibration, noise, and uneven load distribution in gear transmission. By analyzing gear meshing contact, accurate performance data can be obtained, leading to optimization solutions for gear systems.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Interdisciplinary Applications
Omar D. Mohammed, Akshay D. S. Bhat, Peter Falk
Summary: In this article, a structured approach combining meta-models and robust optimization is developed to effectively change the tooth flank contact pattern. This approach can reduce noise, vibration, and harshness (NVH) while improving the durability of gears. By using this method, a unique optimal design solution can be obtained.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Engineering, Mechanical
Emna Ben Younes, Christophe Changenet, Jerome Bruyere, Emmanuel Rigaud, Joel Perret-Liaudet
Summary: This study implemented multi-objective optimization for a gear unit using a genetic algorithm, aiming to minimize power loss and vibration generated by meshing while adjusting macro and micro-geometry parameters of the gears. The results showed that optimizing both micro and macro-geometry parameters simultaneously yielded different outcomes compared to optimizing them separately.
MECHANISM AND MACHINE THEORY
(2022)
Article
Engineering, Mechanical
Suchul Kim, Geunho Lee, Sanggon Moon, Jaeseung Kim, Jaehoon Choi, Chan-ho Choi, Houngjong Ahn, Jonghyeon Sohn
Summary: This paper proposes an efficient process of macro geometry optimization of helical gear pairs using Loaded tooth contact analysis (LTCA). By dividing the LTCA model into different types and adjusting the fidelity, an efficient LTCA method is found. Optimization processes are designed based on the analysis results, and it is found that starting with the model considering only the extended contact and ending 5%-10% of the entire optimization process with the highest fidelity model is the most efficient.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2023)
Article
Multidisciplinary Sciences
Wen Xin, Yanyan Zhang, Yang Fu, Wei Yang, Huanping Zheng
Summary: This study proposes a two-stage computational framework that combines response surface methodology and multi-objective optimization to optimize the radiated noise and weight of a large mining planetary gear reducer. By using a unified experimental design and performing multi-objective optimization using the non-dominated sorting genetic algorithm II (NSGA-II), the research demonstrates the effectiveness of the proposed optimization method in reducing vibrating amplitude and weight of the gearbox.
SCIENTIFIC REPORTS
(2023)
Article
Thermodynamics
Kihan Kwon, Junhyeong Jo, Seungjae Min
Summary: In the development of electric vehicles, multi-speed transmissions are an alternative to single-speed transmissions that require optimization of gear ratios and shifting patterns. The transmission efficiency depends on torque, speed, and drive gear, directly impacting the optimal design. By considering variable transmission efficiency, energy efficiency and dynamic performance can be improved compared to single-speed transmissions.
Article
Engineering, Mechanical
Jony Javorski Eckert, Fabio Mazzariol Santiciolli, Ludmila C. A. Silva, Franco Giuseppe Dedini
Summary: This study presents a multi-objective optimization approach to improve vehicle fuel consumption and acceleration performance while reducing emissions, with a focus on robustness under different driving conditions. The optimization achieved a best-compromised solution through the iAWGA algorithm, showcasing improvements in acceleration performance, fuel efficiency, and emissions reduction.
MECHANISM AND MACHINE THEORY
(2021)
Article
Engineering, Electrical & Electronic
Mengyu Ma, Chao Wang, Zuxing Li, Geyong Min
Summary: This article investigates the efficient transmission design problem in a typical vehicle-to-vehicle (V2V) communication network, where multiple source-destination pairs with different types of message transmission requirements coexist and the network environment dynamically changes. A sequential transmission decision framework based on the multi-objective optimization (MOO) theory is proposed to maximize the performance of each link, while ensuring the QoS of different messages.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Energy & Fuels
A. K. Aadhithiyan, K. V. J. Bhargav, R. Sreeraj, S. Anbarasu
Summary: This research focuses on optimizing the thermal-static performance of LaNi5-holding helically coiled hydride reactors using a combination of response surface methodology, computational modeling, and a desirability approach. The optimal helical reactor design, integrated with a heat exchanger, improves the thermal performance significantly. This study is important for designing accurate and appropriate objective-based hydride reactors.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Automation & Control Systems
Yuhong Li, Ni Li, Guanghong Gong, Jin Yan
Summary: The paper proposes an intelligent design of experiment algorithm using an improved evolutionary multi-objective optimization approach, which shows better sampling capacity and fine sampling efficiency compared to existing algorithms. The application effects of a complex flight simulator demonstrate the algorithm's wide technological prospect in serving certain complex systems well.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Agriculture, Multidisciplinary
Chanho Choi, Houngjong Ahn, Jihun Yu, Jung-Su Han, Su-Chul Kim, Young-Jun Park
Summary: The study optimized the gear macro-geometry of a 75-kW agricultural tractor transmission using a genetic algorithm to minimize transmission errors and reduce gear whine noise. The evaluation and comparison of noise levels showed an overall reduction of 3.1 dBA in the transmission operating range, effectively reducing noise levels of gear harmonic components.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Engineering, Electrical & Electronic
Zixuan Xiang, Xiaoyong Zhu, Min Jiang, Li Quan
Summary: In this article, an objective-layered optimization strategy is proposed for magnetic planetary gear (MPG). Sensitivity analysis is utilized to comprehensively consider the relationships between objectives and parameters. The optimization process is divided into two layers using multi-objective genetic algorithm and double-side PM shaping method. The harmonic analysis of MPG's characteristics and experimental results verify the effectiveness of the proposed optimization strategy.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2022)
Article
Chemistry, Multidisciplinary
Milos Sedak, Bozidar Rosic
Summary: This research addresses the constrained multi-objective nonlinear optimization problem of planetary gearboxes using a hybrid metaheuristic algorithm. The proposed algorithm successfully obtains solutions of the non-convex Pareto set for optimizing weight, efficiency, and preventing premature gear failure. Compared to other well-known algorithms, it shows improved optimization performance in obtaining Pareto solutions.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Multidisciplinary
Milos Sedak, Maja Rosic
Summary: This paper proposes a modified hybrid algorithm, named HMOBPSO, to solve the challenging multi-objective optimization problem of a planetary gearbox. The proposed algorithm integrates PSO and BOA algorithms to improve performance. It can obtain non-convex Pareto optimal solutions, reduce gear weight and improve efficiency, and avoid early failure. Experimental results show significant improvements in gearbox size, efficiency, and spacing compared to conventional methods.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Zongzhuo Yan, Tao Tao, Hongyang Du, Hu Shi, Xuesong Mei
Summary: Due to the special design of slant bed CNC lathes, the temperature of the X-axis feed motor will significantly increase after power-up, even if there is no feed motion. Based on this phenomenon, experiments were redesigned to study the effects of ambient temperature variations, heat generated in the spindle, and heat generated in the X-axis feed system on thermal errors. The results of these experiments provide a reliable reference for thermal error modeling under complicated operating conditions. A new experiment-based multi-objective modeling method, using the multi-objective particle swarm optimization (MOPSO) algorithm, was proposed and showed improved accuracy and reasonability in predicting thermal errors.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
