本文選題：車聯(lián)網(wǎng) + 電動汽車　； 參考：《北京郵電大學(xué)》2016年碩士論文

【摘要】：電動汽車作為綠色環(huán)保的新能源交通工具已受到各國的廣泛關(guān)注,隨著分時租賃新型商業(yè)模式的不斷推廣,電動汽車正在慢慢滲透進民眾的生活,成為大眾綠色出行的新選擇。分時租賃運營模式下的車輛使用時長短、高峰時段集中、支持異地還車等特點顯著,經(jīng)典的車輛租賃調(diào)度算法便不再很好地適用。目前已有的電動汽車調(diào)度算法也較為簡略和籠統(tǒng),典型算法為受限調(diào)度與控制調(diào)度兩類,受限調(diào)度算法不支持跨站調(diào)度;控制調(diào)度算法單一地將運營收益作為車輛調(diào)度和分配策略的主要指標。這兩種調(diào)度算法在分時租賃場景下都具有相當?shù)木窒扌?因此電動汽車分時租賃調(diào)度策略算法的優(yōu)化和完善存在很大空間。本論文以電動汽車運營服務(wù)支撐環(huán)境和分時租賃平臺為依托,針對已有調(diào)度算法的局限性,從服務(wù)率、車輛日均用車時間分布、運營收益和平均調(diào)度距離等各方面進行優(yōu)化與改進,提出了基于多目標最優(yōu)化模型的“全服務(wù)”調(diào)度模式,并以北京綠狗租車分時租賃系統(tǒng)的站點網(wǎng)絡(luò)和車輛信息為仿真環(huán)境和數(shù)據(jù)集,仿真驗證和分析了算法的有效性。同時,本文還系統(tǒng)的介紹了“全服務(wù)”車輛調(diào)度與推薦分配策略下的電動汽車分時租賃平臺的設(shè)計與實現(xiàn)。論文首先概要性地介紹了電動汽車分時租賃的商業(yè)模式,之后詳細介紹了本文的創(chuàng)新性算法——“全服務(wù)”車輛調(diào)度和推薦策略,從算法的需求分析、問題描述、數(shù)學(xué)建模、仿真與結(jié)果分析等方面進行了詳盡描述。接下來,按照軟件工程的流程,對基于“全服務(wù)”車輛調(diào)度和推薦策略的分時租賃平臺進行了細致的需求分析、系統(tǒng)總體設(shè)計、詳細設(shè)計與實現(xiàn)、測試與驗證等。論文結(jié)尾對全文工作進行了梳理總結(jié),并提出了下一步的研究方向。
[Abstract]:As a new energy transportation tool for green and environmental protection, electric vehicles have attracted wide attention from all countries. With the continuous promotion of new type of time leasing business model, electric vehicles are slowly infiltrating into the lives of the people, becoming a new choice for the mass green travel. The classic vehicle rental scheduling algorithm is no longer well applicable. The existing scheduling algorithms for electric vehicles are also relatively simple and general. The typical algorithms are limited scheduling and control scheduling, and the limited scheduling algorithm does not support the cross station scheduling; the control scheduling algorithm uses the operating income as a vehicle to tune a single vehicle. The main index of degree and allocation strategy. The two scheduling algorithms have considerable limitations in the time sharing rental scenario. Therefore, there is a lot of space for the optimization and improvement of the algorithm for the time sharing and scheduling of electric vehicles. This paper is based on the support environment of the electric vehicle operation service and the time sharing lease platform. Limitations are optimized and improved from service rate, vehicle daily vehicle time distribution, operating income and average scheduling distance. A "full service" scheduling model based on multi-objective optimization model is proposed, and the site network and vehicle information of the Beijing green dog renting time rental system are simulated as the simulation environment and data set, and the simulation is simulated. The effectiveness of the algorithm is verified and analyzed. At the same time, the design and implementation of the "full service" vehicle scheduling and the recommendation allocation strategy for the time sharing rental platform for electric vehicles is introduced in this paper. First, the paper briefly introduces the business model of the time sharing lease for electric vehicles, and then introduces the innovative algorithm in detail. "Full service" vehicle scheduling and recommendation strategies are described in detail from the requirements analysis, problem description, mathematical modeling, simulation and result analysis in the algorithm. Next, detailed requirements analysis is made for the time sharing rental platform based on the "full service" vehicle scheduling and recommendation strategy. Design, detailed design and implementation, testing and verification. At the end of the paper, the whole work is summarized, and the next research direction is put forward.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.3

【參考文獻】

相關(guān)期刊論文 前5條

1 任美林;樊春燕;;淺析電動汽車的分時租賃商業(yè)模式[J];科技與創(chuàng)新;2015年22期

2 肖曉偉;肖迪;林錦國;肖玉峰;;多目標優(yōu)化問題的研究概述[J];計算機應(yīng)用研究;2011年03期

3 王之君;張展;;云計算在企業(yè)管理中的應(yīng)用[J];中國石油企業(yè);2011年Z1期

4 周逢權(quán);連湛偉;王曉雷;楊校輝;徐怡山;;電動汽車充電站運營模式探析[J];電力系統(tǒng)保護與控制;2010年21期

5 薛洪波;倫淑嫻;;粒子群算法在多目標優(yōu)化中的應(yīng)用綜述[J];渤海大學(xué)學(xué)報(自然科學(xué)版);2009年03期

相關(guān)重要報紙文章 前1條

1 ;電動汽車分時租賃正向你走來[N];北京日報;2014年

，

本文編號：2002008