Research on parameters matching and optimization method of power transmission system for electric logistics vehicle

Wang, Zongze; Ke-li, Zhao; Su, Li-Da

doi:10.1088/1742-6596/2005/1/012033

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…In addition to carbon dioxide, the internal combustion engine of a traditional car also emits a series of pollutants, such as carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). These pollutants are harmful to air quality and human health, especially in the case of urban traffic congestion [6] .…”

Section: Pollutant Emissionsmentioning

confidence: 99%

New-Energy Vehicle Transmission System Optimization and Design

Zai

2023

JERA

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This paper discusses the optimization and design of the new-energy vehicle transmission systems. Traditional automatic transmission systems suffer from fuel consumption and emissions issues, as well as limitations in the efficiency of mechanical transmission systems. In order to solve these problems, different types of transmission systems are used in new-energy vehicles, including battery electric vehicles (BEV), hybrid electric vehicles (HEV), and fuel cell electric vehicles (FCEV). The key factors for optimizing the transmission systems of new-energy vehicles include battery technology and energy management system, electric motor and electronic control system, energy recovery and reuse technology, and lightweight and aerodynamic design of the vehicle. This paper also introduces methods and tools for designing new-energy vehicle transmission systems, including simulation tools, optimization algorithms and data analysis, as well as experimental verification and testing methods. Besides, new-energy vehicle transmission system designs are proposed, and future challenges and development directions are discussed through case studies.

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Section: Pollutant Emissionsmentioning

confidence: 99%

New-Energy Vehicle Transmission System Optimization and Design

Zai

2023

JERA

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Dynamic Route Optimization for Chinese E-Commerce Logistics Based on Ant Colony Algorithm

Zhou

2023

Applied Mathematics and Nonlinear Sciences

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The limited nature of logistics and distribution vehicles and the variability of customer acceptance service time limit the service efficiency and quality of logistics and distribution. To optimize a logistics distribution path under capacity and time window constraints, a mathematical model of the problem is first developed in this study, with the lowest cost as the model’s objective function. The logistics distribution issue with soft time windows is then addressed using an ant colony algorithm, and a logistics path optimization strategy based on the maximum minimal ant colony system is suggested. Then, the heuristic function is rebuilt to improve the ant colony algorithm’s solution speed, and the pheromone update approach is included. Finally, experimental approaches are used to test the model’s and optimization algorithm’s efficacy for customer sizes of 30, 50, and 100. The experimental results show that the optimized ant colony algorithm has the best value of 2 for α and 3 for β, which can converge earlier. The improved ant colony algorithm also finds the best solution faster than the conventional ant colony method in just 23 rounds. In the mathematical model of the logistics distribution path optimization issue, this study suggests that the optimized ant colony method has the optimization algorithm’s rationality, efficacy, and stability.

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Research on parameters matching and optimization method of power transmission system for electric logistics vehicle

Cited by 2 publications

References 3 publications

New-Energy Vehicle Transmission System Optimization and Design

New-Energy Vehicle Transmission System Optimization and Design

Dynamic Route Optimization for Chinese E-Commerce Logistics Based on Ant Colony Algorithm

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