臺灣博碩士論文加值系統

近年來，隨著環保意識的抬頭，一種嶄新的運具──電動車，已逐漸獲得許多關注。由於電動車所使用的能源是電力，是可再生且對環境較為友善之能源，因此各國無不致力於電動車的普及化，而臺灣也不例外。然而，電動車的普及化有著以下兩大挑戰：電動車本身所受限的行駛續航力與其所使用的昂貴電池。受限的行駛續航力讓使用者在一段使用期間內就必須進行補給能源，進而產生旅程焦慮的問題。因此，輔助設備──能源補給設施對電動車系統來說是不可或缺的，其選址的適當與否也相當重要。事實上，目前已有許多型態的補給方式，其中一種新興且前景看好的方式便是換電系統。換電系統將整個能源補給的時間，從數個小時降低至數分鐘甚至是數秒。這項人性化的優點讓使用者更可能在旅途中就直接執行能源補給。但與此同時，此項優點卻也提高了對備用電池的需求。因此，營運者不只要慎選電池交換站的位置，也要決定它們所對應到的站體大小。然而，要直接決定交換站點的地點與容量大小相當地困難，故本研究的目的是針對換電系統，發展出一套能源補給設施布設規劃的模式。此外，由於臺灣的運輸工具以機車為大宗，故本研究將以電動機車作為主要的研究對象。為了提升模式的可應用性以及方便描繪使用者行為，本研究之研究方法結合了基因演算法與離散型事件模擬，並利用此二法組成了二階規劃。並且，考量到使用者的換電習慣，此模式將採用流量攔截的概念。
在經過一系列實驗性的敏感度分析後，發現到不同的參數對不同形狀的需求空間分布有著不一樣的影響。較為均勻的分布對於預算較為敏感，而電池的消耗率則對離異的需求分布產生較大的影響，其中值得一提的是，電動機車的行駛續航力對兩種形狀的需求分布皆有著極大的影響力。根據真實的案例分析，則找到了一些針對此類換電系統在設置上的準則，如下所述：本研究建議正著手換電站規劃之營運者應以整個交通「流」作為考量，而非僅以交通「區」單點作規劃。此外，營運者應先不顧旅次分布的形狀，優先設置靠近高流量的候選點。再者，考量到使用者的最大可容忍換電時間，營運者的設站策略，應以各交通起迄點為圓心，呈輻射狀設站。
本研究所提出的模式考量了許多重要的因子，其中包括需求不確定性、行駛續航力、使用者的忍受度、使用習慣以及隨充電時間而變化的充電量。此模式為首個同時考量上述因子的模式。此外，透過進行實驗與實際案例的分析，顯現了此一模式的效用與合理性，而這些結果亦點出了考量使用行為的重要性。因此，此模式可作為輔助電動機車換電系統營運者決策一適當換電站布局的工具。

In recent years, along with raising environmental consciousness, an innovative transportation mode—electric vehicles have gotten many attentions. Because the power source of electric vehicles is electric power, a renewable and environmentally friendly energy, worldwide countries have been devoted to the popularization of electric vehicles and Taiwan is no exception. However, there are two principal challenges for the penetration of electric vehicles: the limited endurance of the mode and its expensive batteries. The limited endurance lets the user has to refuel the energy during a certain using period and the problem of range anxiety comes out. Hence, an auxiliary equipment—the refueling facility is necessary for electric vehicles and it is essential to locate the charger appropriately. Actually, there already are many types of refueling methods and one of the innovative and promising ways is the swapping system. The swapping system reduces the entire refueling time from original several hours to a few minutes or even seconds. This user-friendly advantage lets the user conducts the refueling on the road become much more possible but on the other side, this benefit also increases the need for spare batteries. Therefore, not only the location but also the capacity of swapping stations has to be cautiously determined by the operator. Nevertheless, it is thorny to decide where and how big the swapping station should be directly, so the purpose of this research is to develop a model for deploying the refueling facilities of the swapping system. In addition, because the most popularized transportation mode in Taiwan is scooters, the research object of this study is electric scooters. In order to enhance the applicability of the model and depict the usage behavior conveniently, the methodology adopted in this study combines the genetic algorithm and the discrete-event simulation forming a two-stage planning. In addition, considering the usage habits of the swapping system, the notion of flow interception is adopted in the model.
After the sensitivity analysis of experiments, it is found that different parameters have diverse impacts on different shapes of demand spatial distribution. Regular spatial distribution is much more sensitive to the budget and the irregular one is sensitive to the power consumption rate of batteries. Noteworthily, a factor significantly influencing both the shape of demand distribution is the driving endurance. With the case study in the reality, some setting instructions for such a location problem have been obtained. The operator who is going to plan a layout for swapping stations should adopt the entire traffic “flow” rather than the traffic “zone”. Besides, the operator should give a locating priority to the station where is near heavy traffic flows regardless of the shape of demand distributions. Further, considering the user’s maximum tolerable driving distance for swapping, the operator should radially deploy the station taking origins and destinations as the center.
Many important factors are considered in the model such as the demand uncertainty, driving endurance, the tolerance of the user, usage behavior and the varied charging power levels by charging time. This is the first time that a model takes these significant factors into account at the same time. What’s more, after the experiments and the case study, the utility and validity of the model are exhibited and these results also show the importance of considering usage behavior. Thus, this model can be a useful tool to help the operator to decide a proper deployment of swapping stations for electric scooters.

口試委員會審定書 #
誌謝 ii
摘要 iii
ABSTRACT v
CONTENTS vii
LIST OF FIGURES ix
LIST OF TABLES xii
Chapter 1 Introduction 1
1.1 Motivation and Background Information 1
1.2 Research Purpose 3
1.3 Overview 4
Chapter 2 Literature Review 7
2.1 Battery Charging System 7
2.2 Battery Swapping System 10
2.3 Electric Vehicle and Electric Scooters 14
2.4 Summary 15
Chapter 3 Methodology 19
3.1 Problem Statement 19
3.2 Model Formulation 21
3.2.1 Genetic Algorithm 22
3.2.2 Stochastic Discrete-Event Simulation (SDES) 22
3.2.2.1 Model Overview 22
3.2.2.2 Objective Function 25
3.2.2.3 Object-oriented Programming 28
Chapter 4 Results 38
4.1 Input Data and General Parameter Setting 39
4.2 Experiment 44
4.2.1 Regular Spatial Distribution of Demand 44
4.2.2 Irregular Spatial Distribution of Demand 62
4.2.2.1 Sensitivity Analysis of the Irregular Spatial Distribution 64
4.2.3 Findings of the Experiments 77
4.3 Case Study 81
4.3.1 Subject’s Background 81
4.3.2 The Procedure of Collecting Input Data 83
4.3.3 Parameter Setting for the Genetic Algorithm 86
4.3.4 Output and Findings of Case Study 90
4.3.4.1 Setting Guidelines 90
4.3.4.2 The Effects of Usage Habits 100
Chapter 5 Discussion 106
5.1 Conclusion 106
5.2 Limitations 109
5.3 Future Work 111
REFERENCES 113
APPENDIX 116

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