WO2016180004A1 - 一种多充电节点的无线传感器网络充电方法 - Google Patents
一种多充电节点的无线传感器网络充电方法 Download PDFInfo
- Publication number
- WO2016180004A1 WO2016180004A1 PCT/CN2015/095390 CN2015095390W WO2016180004A1 WO 2016180004 A1 WO2016180004 A1 WO 2016180004A1 CN 2015095390 W CN2015095390 W CN 2015095390W WO 2016180004 A1 WO2016180004 A1 WO 2016180004A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- charging
- sensor
- energy
- alarm
- node
- Prior art date
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/50—Charging stations characterised by energy-storage or power-generation means
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/14—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle
- H02J7/1423—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle with multiple batteries
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3206—Monitoring of events, devices or parameters that trigger a change in power modality
- G06F1/3212—Monitoring battery levels, e.g. power saving mode being initiated when battery voltage goes below a certain level
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
- H01M10/4257—Smart batteries, e.g. electronic circuits inside the housing of the cells or batteries
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/40—The network being an on-board power network, i.e. within a vehicle
- H02J2310/48—The network being an on-board power network, i.e. within a vehicle for electric vehicles [EV] or hybrid vehicles [HEV]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
- H02J7/00034—Charger exchanging data with an electronic device, i.e. telephone, whose internal battery is under charge
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/14—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle
- H02J7/143—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle with multiple generators
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/14—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle
- H02J7/1446—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from dynamo-electric generators driven at varying speed, e.g. on vehicle in response to parameters of a vehicle
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/14—Plug-in electric vehicles
Definitions
- the present invention relates to the field of wireless sensor network energy transmission, and in particular to a wireless sensor network charging method for a multi-charging node.
- Wireless sensor networks are mostly used in the monitoring field. Hundreds of sensors deployed in the network are used to collect data and transmit the data to the base station directly or via multiple hops through its own communication module. The base station aggregates the information and transmits it to the monitoring personnel. To achieve the purpose of monitoring. The information transfer process involves the processing, fusion, and inter-node communication of data, which are the most important sources of sensor energy consumption.
- the research on the related charging methods of wireless sensor networks deploying multiple charging trolleys mainly involves two aspects: one is the shortest path selection for minimizing the total cost, and the other is the scheduling of multiple charging trolleys.
- the present invention proposes a wireless sensor network charging method of a multi-charging node.
- the wireless sensor network charging method of the multi-charging node of the present invention is an adaptive charging method designed based on the independence of each charging trolley.
- the adaptive charging method is in a wireless sensor network WSNs, each charging car does not affect each other, is independent of each other, each performs a charging task in the domain, and can automatically select the starting time of the charging trip, each time a charging task is completed, The above work will be repeated, and is not limited by the time slot conditions, nor is it affected by other charging cars.
- the method complexity is also limited to the complexity level of the method when deploying a charging trolley.
- a wireless sensor network charging method for a multi-charging node includes the following steps: including the following steps:
- the sensor carrying battery capacity is B
- the energy consumption rate of the jth sensor is ⁇ j
- the low energy alarm threshold is M j
- M j ⁇ B, 0 ⁇ 1, ⁇ indicates the low energy alarm threshold M j
- the percentage of sensor energy B is
- q is The number of charging trolleys; the base station is used to collect sensor information and communicate with the charging trolley; the parking lot is used to replenish energy for the charging trolley; the battery capacity of each charging trolley is E, the moving speed is a stable value S, and each charging trolley gives one
- the sensor charging time is a fixed value C;
- Each charging cart performs a charging task.
- step (2) the specific steps of dividing the domain range of each charging trolley are:
- Decomposing the minimum spanning tree ⁇ Decompose the minimum spanning tree into q disjoint rooted trees with q parking lots as the root node.
- the upper limit of the total number of nodes in each rooted tree is: Where A is the total number of sensor nodes in the sensor network, and q is the number of charging cars. The representative is rounded up; A represents the total number of sensor nodes in the sensor network;
- step (3) the specific steps of each charging trolley to perform the charging task are:
- the charging car starts to receive the alarm signal from the low-energy sensor. After the charging car receives the alarm signal, it updates the value of l, j, and generates the shortest charging path s l for each l value. The charging car calculates the energy discrimination vector Q, l The total number of alarm sensor nodes received, j is the alarm sensor node number;
- the charging car judges whether it needs to return to the parking lot to replenish energy. If necessary, the charging car returns to the parking lot to replenish energy; otherwise, it returns to step (3.2).
- the shortest charging path s l is generated by: all the alarm sensor sets are Taking the charging trolley as the starting point, one path e m with the smallest Euclidean distance value is selected among the l paths connected to the charging trolley, and e m is connected to the charging trolley and another alarm sensor node. Sensor node As a starting point, a path e n with the smallest Euclidean distance value is selected among the remaining l-1 paths except the removal path e m connected thereto, and the e n is connected to the alarm sensor node. And alarm sensor nodes By analogy, a shortest charging path s l passing through the charging sensor node starting from the charging trolley is obtained.
- the energy discriminant vector Q has the meaning of: assuming that the charging task is started when one alarm signal is received, and the least remaining energy is arranged in the case where the j-th alarmed sensor node is finally charged.
- M j the low energy alarm threshold
- M j 20% B
- B represents the battery capacity of each sensor
- ⁇ j the energy consumption rate of the jth alarmed sensor node
- l the received alarm
- the total number of sensor nodes D is the total length of the shortest charging path corresponding to l
- S is the moving speed of the charging car
- C is the time required to charge each sensor
- C is a constant value
- t is the current state of the charging car calculation vector element At the moment, t j is the alarm moment of the jth alarm sensor node recorded by the charging cart.
- the charging car determines whether it needs to return to the parking lot to supplement the energy according to the following: the residual energy of the trolley E ⁇ ⁇ 5%E, and the E ⁇ is assumed that the charging car performs the charging task again and returns to the parking.
- the remaining energy after the field, E is the battery capacity of the car;
- E ⁇ is the remaining energy of the car at the moment of judgment. For the energy consumed by the car to return to the parking lot from the position where the charging task is completed again, ⁇ Q is the additional energy loss caused by the car being affected by the external environment, and Q c is the expected energy consumption for the recharging task;
- B' l'+1 is the remaining energy of the l'+1th alarm sensor node
- B' l'+2 is the remaining energy of the l'+2 alarm sensor nodes
- B' l' is the l'th The remaining energy of the alarm sensor node
- B represents the sensor carrying battery energy.
- the invention has the following advantages:
- the energy consumption rate and residual energy of the sensor can be taken into account in a unified manner.
- the time condition limitation caused by the fixed time slot charging can be removed, and the charging strategy can be adaptively changed according to the change of the sensor energy information in the network.
- FIG. 1 is a flow chart of a method for charging a wireless sensor network according to the present invention
- FIG. 2 is a block diagram showing the steps of dividing the field range of each charging cart according to the present invention.
- a wireless sensor network charging method for a multi-charging node includes the following steps: including the following steps:
- the sensor carrying battery capacity is B
- the energy consumption rate of the jth sensor is ⁇ j
- the low energy alarm threshold is M j
- M j ⁇ B, 0 ⁇ 1, ⁇ indicates the low energy alarm threshold M j
- the percentage of sensor energy B is
- q is The number of charging trolleys; the base station is used to collect sensor information and communicate with the charging trolley; the parking lot is used to replenish energy for the charging trolley; the battery capacity of each charging trolley is E, the moving speed is a stable value S, and each charging trolley gives one
- the sensor charging time is a fixed value C;
- Each charging cart performs a charging task.
- step (2) the specific steps of dividing the domain range of each charging trolley are:
- Decomposing the minimum spanning tree ⁇ Decompose the minimum spanning tree into q disjoint rooted trees with q parking lots as the root node.
- the upper limit of the total number of nodes in each rooted tree is: Where A is the total number of sensor nodes in the sensor network, and q is the number of charging cars. The representative is rounded up; A represents the total number of sensor nodes in the sensor network;
- step (3) the specific steps of each charging trolley to perform a charging task are:
- the charging car starts to receive the alarm signal from the low-energy sensor. After the charging car receives the alarm signal, it updates the value of l, j, and generates the shortest charging path s l for each l value. The charging car calculates the energy discrimination vector Q, l The total number of alarm sensor nodes received, j is the alarm sensor node number;
- step (3.5) The charging car judges whether it needs to return to the parking lot to replenish energy, if necessary, then The charging trolley returns to the parking lot to replenish energy; otherwise, returns to step (3.2).
- the shortest charging path s l is generated by: all the alarm sensor sets are Taking the charging trolley as the starting point, one path e m with the smallest Euclidean distance value is selected among the l paths connected to the charging trolley, and e m is connected to the charging trolley and another alarm sensor node. Sensor node As a starting point, a path e n with the smallest Euclidean distance value is selected among the remaining l-1 paths except the removal path e m connected thereto, and the e n is connected to the alarm sensor node. And alarm sensor nodes By analogy, a shortest charging path s l passing through the charging sensor node starting from the charging trolley is obtained.
- the meaning of the energy discriminant vector Q is: assuming that the charging task is started when one alarm signal is received, and the minimum remaining energy is arranged in the case where the j-th alarmed sensor node is finally charged. Vector.
- M j the low energy alarm threshold
- M j 20% B
- B represents the battery capacity of each sensor
- ⁇ j the energy consumption rate of the jth alarmed sensor node
- l the received alarm
- the total number of sensor nodes D is the total length of the shortest charging path corresponding to l
- S is the moving speed of the charging car
- C is the time required to charge each sensor
- C is a constant value
- t is the current state of the charging car calculation vector element At the moment, t j is the alarm moment of the jth alarm sensor node recorded by the charging cart.
- the charging car judges whether it needs to return to the parking lot to replenish energy according to the following: the residual energy of the trolley E ⁇ ⁇ 5%E, E ⁇ is assumed that the charging car performs the charging task again and returns to the parking lot.
- the remaining energy, E is the battery capacity of the car;
- the E ⁇ calculation basis is: Where E' is the remaining energy of the car at the moment of judgment, For the energy consumed by the car to return to the parking lot from the position where the charging task is completed again, ⁇ Q is the additional energy loss caused by the car being affected by the external environment, and Q c is the expected energy consumption for the recharging task;
- B' l'+1 is the remaining energy of the l'+1th alarm sensor node
- B' l'+2 is the remaining energy of the l'+2 alarm sensor nodes
- B' l' is the l'th The remaining energy of the alarm sensor node
- B represents the sensor carrying battery energy.
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
一种多充电节点的无线传感器网络充电方法,包括如下步骤:(1)建立一个WSNs模型:(2)划分充电小车的领域范围;(3)各充电小车进行充电:(a)初始化:l=0,j=0,l为接收到的报警节点总数,j为已报警节点编号;(b)接收报警信号,更新l,j的值,生成最短充电路径sl,计算能量判别向量;(c)若向量元素出现Qlj≤5%B,j=1,2,…,l,则对l个报警节点按对应最短充电路径sl执行充电任务,否则返回继续更新l,j值;(d)执行充电任务;(e)判断充电小车是否需要返回停车场补充能量,若需要,则充电小车返回停车场补充能量,否则,返回继续更新l,j值及向量元素Qlj。本发明能依据传感器能量变化自适应的改变充电策略;各充电小车相互独立,简单可靠。
Description
本发明涉及无线传感器网络能量传输领域,特别是涉及一种多充电节点的无线传感器网络充电方法。
基于磁谐振和磁耦合的无线能量传输技术的发展,以及近些年在超快充电电池材料研究方面的突破,使得在无线传感器网络中部署移动的充电节点(又称充电小车)来实现网络中传感器能量补充的研究备受关注。
无线传感器网络大多应用于监测领域,网络中部署的成百上千的传感器被用于采集数据并将数据通过自身通信模块直接或者经多跳传递给基站,由基站把信息汇总并传递给监测人员,达到监测目的。信息传递过程包含了数据的处理、融合以及节点间通信,这些都是传感器能量消耗最主要的来源。
为保障监测周期内无线传感器网络(WSNs)的持久工作,网络中传感器能量不至于耗尽,必须建立一种实用而有效的方法来对网络中传感器节点实时充电,并实现充电小车最优调度,使得每次充电任务中充电小车的总耗费最少。
2011年,Y.Shi在文献On renewable sensor networks with wireless energe transfer.Proc.of INFOCOM,IEEE,2011中提出在WSNs中,部署一个充电小车,通过周期性地拜访网络中的每个传感器来实现传感器能量的补充,其时隙固定,使用受到限制。
对于部署多个充电小车的无线传感器网络的相关充电方法的研究,主要涉及两个方面的问题:一是为使总耗费最少而进行的最短路径选取,二是多个充电小车的行程安排。
发明内容
为摆脱传统方法中由于固定时隙充电带来的限制,本发明提出了一种多充电节点的无线传感器网络充电方法。
本发明之多充电节点的无线传感器网络充电方法是基于各充电小车的独立性而设计的自适应充电方法。
自适应充电方法是在一个无线传感器网络WSNs中,各充电小车之间互不影响,相互独立,各自在领域范围内执行充电任务,并能够自动选择充电行程的开始时间,每完成一次充电任务,会重复以上工作,并不受时隙条件的限制,也不受其他充电小车的影响。
由于各个充电小车之间相互独立,方法复杂度也会局限在部署一个充电小车时方法的复杂度等级。
本发明所采用的技术方案是:
一种多充电节点的无线传感器网络充电方法,包括如下步骤:包括如下步骤:
(1)建立一个WSNs模型:在一大片监测区域内随机部署成百上千个传感器,q个充电小车以及对应的q个停车场,监测周期为T;
传感器构成的集合为V,即:V={v1,v2,v3......},v1、v2、v3分别代表第一、第二、第三个传感器;每个传感器携带电池容量均为B,第j个传感器的能量消耗率为ρj,低能报警阈值为Mj,且Mj=α·B,0<α<1,α表示低能报警阈值Mj占传感器能量B的百分比;
i为充电小车编号,停在停车场所在位置ri,ri=(xi,yi),1≤i≤q,xi、yi分别表示位置ri的二维地图坐标,q为充电小车的个数;基站用于收集传感器信息,与充电小车通信;停车场用来为充电小车补充能量;各充电小车的电池容量均为E,移动速度为稳定值S,各充电小车给一个传感器充电时间为固定值C;
(2)划分每个充电小车的领域范围;
(3)各充电小车执行充电任务。
进一步,所述步骤(2)中,划分每个充电小车的领域范围的具体步骤为:
(2.1)生成扩展节点:将传感器网络中的q个充电小车及所在停车场用一闭合的回路η包围起来,回路η内部不包含其他传感器节点,则回路η即为扩展节点;
(2.2)以扩展节点为根节点,传感器节点为树枝节点生成最小生成树ψ;
(2.3)分解最小生成树ψ:以q个停车场为根节点,将最小生成树分解为q个不相交的有根树,每个有根树的节点总数上限为:其中A为传感器网络中传感器节点的总数,q为充电小车的个数,代表向上取整;A代表传感器网络中传感器节点总数;
进一步,所述步骤(3)中,各充电小车执行充电任务的具体步骤为:
(3.1)充电小车接收报警传感器节点总数及已报警节点编号,并初始化:l=0,j=0,其中l为接收到的报警传感器节点总数,j为已报警传感器节点编号;
(3.2)充电小车开始接收低能传感器发出的报警信号,充电小车接收报警信号后更新l,j的值,并对每个l值生成最短充电路径sl,充电小车计算能量判别向量Q,l为接收到的报警传感器节点总数,j为已报警传感器节点编号;
(3.3)若能量判别向量Q的元素Qlj≤5%B,j=1,2,…,l,其中,l为接收到的报警传感器节点总数,j为已报警传感器节点编号,B代表每个传感器电池容量,则按最短充电路径sl执行步骤(3.4),否则返回步骤(3.2);
(3.4)执行充电任务:即充电小车开始对传感器进行充电;
(3.5)充电小车判断其自身是否需要返回停车场补充能量,若需要,则充电小车返回停车场补充能量;否则,返回步骤(3.2)。
进一步,所述步骤(3.2)中,最短充电路径sl的生成方法为:所有已报警传感器集合为以充电小车为起点,在和充电小车相连的l条路径中选取出欧式距离权值最小的一条路径em,em连接充电小车和另一已报警传感器节点接着以传感器节点为起点,在与其相连的除去路径em外的剩余l-1条路径中选取出欧式距离权值最小的一条路径en,en连接已报警传感器节点和已报警传感器节点以此类推,得到一个以充电小车为起点经过l个待充电传感器节点的最短充电路径sl。
进一步,所述步骤(3.2)中,能量判别向量Q的含义为:假设接收到l个报警信号时开始充电任务,并且安排对第j个已报警传感器节点最后进行充电的情况下其最少剩余能量所组成的向量。
进一步,所述步骤(3.2)中,能量判别向量Q形式为:j=1,2,…,l;能量判别向量的元素Qlj的计算方法是:其中Mj是低能报警阈值,设定阈值为Mj=20%B,
其中B代表每个传感器携带电池容量,ρj是第j个已报警传感器节点的能量消耗率,l为接收到的报警传感器节点总数,D是l所对应的最短充电路径的总长度,S是充电小车的移动速度,C是对每个传感器充电所需时间,C为恒定值,t是充电小车计算向量元素的当前时刻,tj是充电小车所记录的第j个报警传感器节点的报警时刻。
进一步,所述步骤(3.5)中,充电小车判断其自身是否需要返回停车场补充能量的依据为:小车剩余能量Eμ≤5%E,Eμ为假设充电小车再次执行充电任务并回到停车场后的剩余能量,E为小车电池容量;
Qc计算依据为:Qc=λ·D'+(l-l')·B-(B′l′+1+B′l′+2+......B′l),其中λ为单位路程小车的能量耗费,l为接收到报警传感器节点总数,l'表示充电小车作出判断时刻已经解除报警的传感器节点总数,D'为充电小车作出判断时刻对应l生成最短路径的总长度,B′l′+1为第l'+1个报警传感器节点的剩余能量,B′l′+2为第l'+2个报警传感器节点的剩余能量,B′l′为第l'个报警传感器节点的剩余能量,B代表传感器携带电池能量。
本发明与现有技术相比具有如下优点:
(1)传感器能量消耗率和剩余能量能统一考虑在内,不用单独分析,摆脱了固定时隙充电带来的时间条件限制,能依据网络中传感器能量信息的变化自适应的改变充电策略。
(2)使用本发明。各充电小车之间独立,方法复杂度等同于部署一个充
电小车时的方法复杂度,简单可靠。
图1为本发明无线传感器网络充电方法的流程框图;
图2为本发明划分每个充电小车的领域范围步骤框图。
以下结合附图和实施例对本发明进行详细的说明。
一种多充电节点的无线传感器网络充电方法,包括如下步骤:包括如下步骤:
(1)建立一个WSNs模型:在一大片监测区域内随机部署成百上千个传感器,q个充电小车以及对应的q个停车场,监测周期为T;
传感器构成的集合为V,即:V={v1,v2,v3......},v1、v2、v3分别代表第一、第二、第三个传感器;每个传感器携带电池容量均为B,第j个传感器的能量消耗率为ρj,低能报警阈值为Mj,且Mj=α·B,0<α<1,α表示低能报警阈值Mj占传感器能量B的百分比;
i为充电小车编号,停在停车场所在位置ri,ri=(xi,yi),1≤i≤q,xi、yi分别表示位置ri的二维地图坐标,q为充电小车的个数;基站用于收集传感器信息,与充电小车通信;停车场用来为充电小车补充能量;各充电小车的电池容量均为E,移动速度为稳定值S,各充电小车给一个传感器充电时间为固定值C;
(2)划分每个充电小车的领域范围;
(3)各充电小车执行充电任务。
进一步,所述步骤(2)中,划分每个充电小车的领域范围的具体步骤为:
(2.1)生成扩展节点:将传感器网络中的q个充电小车及所在停车场用一闭合的回路η包围起来,回路η内部不包含其他传感器节点,则回路η即为扩展节点;
(2.2)以扩展节点为根节点,传感器节点为树枝节点生成最小生成树ψ;
(2.3)分解最小生成树ψ:以q个停车场为根节点,将最小生成树分解为q个不相交的有根树,每个有根树的节点总数上限为:其中A为传感器网络中传感器节点的总数,q为充电小车的个数,代表向上取整;A代表传感器网络中传感器节点总数;
所述步骤(3)中,各充电小车执行充电任务的具体步骤为:
(3.1)充电小车接收报警传感器节点总数及已报警节点编号,并初始化:l=0,j=0,其中l为接收到的报警传感器节点总数,j为已报警传感器节点编号;
(3.2)充电小车开始接收低能传感器发出的报警信号,充电小车接收报警信号后更新l,j的值,并对每个l值生成最短充电路径sl,充电小车计算能量判别向量Q,l为接收到的报警传感器节点总数,j为已报警传感器节点编号;
(3.3)若能量判别向量Q的元素Qlj≤5%B,j=1,2,…,l,其中,l为接收到的报警传感器节点总数,j为已报警传感器节点编号,B代表每个传感器电池容量,则按最短充电路径sl执行步骤(3.4),否则返回步骤(3.2);
(3.4)执行充电任务:即充电小车开始对传感器进行充电;
(3.5)充电小车判断其自身是否需要返回停车场补充能量,若需要,则
充电小车返回停车场补充能量;否则,返回步骤(3.2)。
所述步骤(3.2)中,最短充电路径sl的生成方法为:所有已报警传感器集合为以充电小车为起点,在和充电小车相连的l条路径中选取出欧式距离权值最小的一条路径em,em连接充电小车和另一已报警传感器节点接着以传感器节点为起点,在与其相连的除去路径em外的剩余l-1条路径中选取出欧式距离权值最小的一条路径en,en连接已报警传感器节点和已报警传感器节点以此类推,得到一个以充电小车为起点经过l个待充电传感器节点的最短充电路径sl。
所述步骤(3.2)中,能量判别向量Q的含义为:假设接收到l个报警信号时开始充电任务,并且安排对第j个已报警传感器节点最后进行充电的情况下其最少剩余能量所组成的向量。
所述步骤(3.2)中,能量判别向量Q的形式为:j=1,2,…,l;能量判别向量的元素Qlj的计算方法是:其中Mj是低能报警阈值,设定阈值为Mj=20%B,其中B代表每个传感器携带电池容量,ρj是第j个已报警传感器节点的能量消耗率,l为接收到的报警传感器节点总数,D是l所对应的最短充电路径的总长度,S是充电小车的移动速度,C是对每个传感器充电所需时间,C为恒定值,t是充电小车计算向量元素的当前时刻,tj是充电小车所记录的第j个报警传感器节点的报警时刻。
所述步骤(3.5)中,充电小车判断其自身是否需要返回停车场补充能量的依据为:小车剩余能量Eμ≤5%E,Eμ为假设充电小车再次执行充电任务并回到停车场后的剩余能量,E为小车电池容量;
Qc计算依据为:Qc=λ·D'+(l-l')·B-(B′l′+1+B′l′+2+......B′l),其中λ为单位路程小车的能量耗费,l为接收到报警传感器节点总数,l'表示充电小车作出判断时刻已经解除报警的传感器节点总数,D'为充电小车作出判断时刻对应l生成最短路径的总长度,B′l′+1为第l'+1个报警传感器节点的剩余能量,B′l′+2为第l'+2个报警传感器节点的剩余能量,B′l′为第l'个报警传感器节点的剩余能量,B代表传感器携带电池能量。
Claims (7)
- 一种多充电节点的无线传感器网络充电方法,其特征在于,包括如下步骤:(1)建立一个WSNs模型:在一大片监测区域内随机部署成百上千个传感器,q个充电小车以及对应的q个停车场,监测周期为T;传感器构成的集合为V,即:V={v1,v2,v3......},v1、v2、v3分别代表第一、第二、第三个传感器;每个传感器携带电池容量均为B,第j个传感器的能量消耗率为ρj,低能报警阈值为Mj,且Mj=α·B,0<α<1,α表示低能报警阈值Mj占传感器能量B的百分比;i为充电小车编号,停在停车场所在位置ri,ri=(xi,yi),1≤i≤q,xi、yi分别表示位置ri的二维地图坐标,q为充电小车的个数;基站用于收集传感器信息,与充电小车通信;停车场用来为充电小车补充能量;各充电小车的电池容量均为E,移动速度为稳定值S,各充电小车给一个传感器充电时间为固定值C;(2)划分每个充电小车的领域范围;(3)各充电小车执行充电任务。
- 根据权利要求1所述的多充电节点的无线传感器网络充电方法,其特征在于,所述步骤(2)中,划分每个充电小车的领域范围的具体步骤为:(2.1)生成扩展节点:将传感器网络中的q个充电小车及所在停车场用一闭合的回路η包围起来,回路η内部不包含其他传感器节点,则回路η即为扩展节点;(2.2)以扩展节点为根节点,传感器节点为树枝节点生成最小生成树ψ;(2.3)分解最小生成树ψ:以q个停车场为根节点,将最小生成树分解为q个不相交的有根树,每个有根树的节点总数上限为:其中A为传感器网络中传感器节点的总数,q为充电小车的个数,代表向上取整;A代表传感器网络中传感器节点总数;
- 根据权利要求1或2所述的多充电节点的无线传感器网络充电方法,其特征在于,所述步骤(3)中,各充电小车执行充电任务的具体步骤为:(3.1)充电小车接收报警传感器节点总数及已报警节点编号,并初始化:l=0,j=0,其中l为接收到的报警传感器节点总数,j为已报警传感器节点编号;(3.2)充电小车开始接收低能传感器发出的报警信号,充电小车接收报警信号后更新l,j的值,并对每个l值生成最短充电路径sl,充电小车计算能量判别向量Q,l为接收到的报警传感器节点总数,j为已报警传感器节点编号;(3.3)若能量判别向量Q的元素Qlj≤5%B,j=1,2,…,l,其中,l为接收到的报警传感器节点总数,j为已报警传感器节点编号,B代表每个传感器电池容量,则按最短充电路径sl执行步骤(3.4),否则返回步骤(3.2);(3.4)执行充电任务:即充电小车开始对传感器进行充电;(3.5)充电小车判断其自身是否需要返回停车场补充能量,若需要,则充电小车返回停车场补充能量;否则,返回步骤(3.2)。
- 根据权利要求3所述的多充电节点的无线传感器网络充电方法,其特征在于,所述步骤(3.2)中,能量判别向量Q的含义为:假设接收到l个报警信号时开始充电任务,并且安排对第j个已报警传感器节点最后进行充电的情况下其最少剩余能量所组成的向量。
- 根据权利要求3所述的多充电节点的无线传感器网络充电方法,其特征在于,所述步骤(3.5)中,充电小车判断其自身是否需要返回停车场补充能量的依据为:小车剩余能量Eμ≤5%E,Eμ为假设充电小车再次执行充电任务并回到停车场后的剩余能量,E为小车电池容量;Qc计算依据为:Qc=λ·D'+(l-l')·B-(B′l′+1+B′l′+2+......B′l),其中λ为单位路程小车的能量耗费,l为接收到报警传感器节点总数,l'表示充电小车作出判断时刻已经解除报警的传感器节点总数,D'为充电小车作出判断时刻对应l生成最短路径的总长度,B′l′+1为第l'+1个报警传感器节点的剩余能量,B′l′+2为第l'+2个报警传感器节点的剩余能量,B′l′为第l'个报警传感器节点的剩余能量,B代表传感器携带电池能量。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US15/536,138 US10110026B2 (en) | 2015-05-12 | 2015-11-24 | Wireless sensor network charging method for multi-charge nodes |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510237380.5 | 2015-05-12 | ||
CN201510237380.5A CN104953643B (zh) | 2015-05-12 | 2015-05-12 | 一种多充电节点的无线传感器网络充电方法 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2016180004A1 true WO2016180004A1 (zh) | 2016-11-17 |
Family
ID=54168097
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2015/095390 WO2016180004A1 (zh) | 2015-05-12 | 2015-11-24 | 一种多充电节点的无线传感器网络充电方法 |
Country Status (3)
Country | Link |
---|---|
US (1) | US10110026B2 (zh) |
CN (1) | CN104953643B (zh) |
WO (1) | WO2016180004A1 (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114301084A (zh) * | 2022-01-11 | 2022-04-08 | 高振国 | 一种方向性无线充电车的传感网充电调度算法 |
Families Citing this family (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104953643B (zh) | 2015-05-12 | 2017-03-08 | 合肥工业大学 | 一种多充电节点的无线传感器网络充电方法 |
CN106403968A (zh) * | 2016-06-06 | 2017-02-15 | 四川大学 | WRSNs中异构移动充电车充电规划方法 |
CN105979488B (zh) * | 2016-07-26 | 2019-05-17 | 河海大学常州校区 | 无线传感器网络中基于区域划分的协同充电算法 |
CN106785131A (zh) * | 2016-11-23 | 2017-05-31 | 南京邮电大学 | 一种无线传感网络节点的充电控制方法 |
CN106877437B (zh) * | 2017-03-15 | 2019-09-10 | 南京邮电大学 | 一种基于多移动充电器的无线传感器网络能量补充方法 |
CN107316100A (zh) * | 2017-06-01 | 2017-11-03 | 四川大学 | 智慧城市中电动汽车的充电调度策略 |
CN107528360B (zh) * | 2017-07-19 | 2019-07-19 | 北京邮电大学 | 无线传感器网络的充电方法及装置 |
CN107592610B (zh) * | 2017-07-28 | 2020-05-15 | 昆明理工大学 | 一种可充电传感器网络的谐振中继器位置确定方法 |
CN107657374B (zh) * | 2017-09-25 | 2021-01-08 | 中南大学 | 一种基于能耗和距离动态变化的按需充电调度方法 |
CN108649286B (zh) * | 2018-05-03 | 2020-01-21 | 南京大学 | 一种基于Powercast模型的WSNs充电方法 |
CN108656989B (zh) * | 2018-05-03 | 2020-04-21 | 南京大学 | 一种针对周期性运动的电动小车的无线交互充电方法 |
CN109275170A (zh) * | 2018-08-20 | 2019-01-25 | 全球能源互联网研究院有限公司 | 一种无线可充电传感网络的充电方法及系统 |
CN109089283B (zh) * | 2018-10-10 | 2022-05-24 | 北京新联铁集团股份有限公司 | 无源无线传感网能量感知管理组件 |
CN110267324A (zh) * | 2019-05-22 | 2019-09-20 | 杭州电子科技大学 | 一种基于中继充电模型最短完成任务时间优化方法 |
CN110248330B (zh) * | 2019-05-22 | 2022-06-14 | 杭州电子科技大学 | 一种基于中继充电模型最大化充电小车休息时间调度方法 |
CN110729783B (zh) * | 2019-10-23 | 2023-05-02 | 吉林大学 | 一种在线可充电传感器网络充电调度系统 |
CN111163479B (zh) * | 2020-01-06 | 2022-08-09 | 广东冠兴科技发展有限公司 | 一种适于无线可定位传感网络的节点优化部署方法 |
CN112751424B (zh) * | 2020-12-29 | 2023-01-31 | 中国矿业大学 | 一种用于综采工作面无线传感节点的边采煤边充电方法 |
CN113068242B (zh) * | 2021-03-29 | 2023-02-03 | 重庆师范大学 | 基于优化量子蚁群算法的路由规划方法及系统 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2533975A1 (en) * | 2005-01-31 | 2006-07-31 | Eaton Corporation | Wireless node and method of powering a wireless node employing ambient light to charge an energy store |
CN102157988A (zh) * | 2011-03-15 | 2011-08-17 | 东南大学 | 一种无线传感器网络节点的无线充供电方法 |
CN102355067A (zh) * | 2011-07-04 | 2012-02-15 | 东南大学 | 一种无线传感器网络节点的移动式无线充供电方法 |
CN202190128U (zh) * | 2011-07-04 | 2012-04-11 | 东南大学 | 一种无线传感器网络节点的移动式无线充供电装置 |
CN103219779A (zh) * | 2013-05-13 | 2013-07-24 | 东南大学 | 一种传感网节点无线充电方法 |
CN104953643A (zh) * | 2015-05-12 | 2015-09-30 | 合肥工业大学 | 一种多充电节点的无线传感器网络充电方法 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9148849B2 (en) * | 2013-06-03 | 2015-09-29 | King Fahd University Of Petroleum And Minerals | Coverage, connectivity and communication (C3) protocol method for wireless sensor networks |
-
2015
- 2015-05-12 CN CN201510237380.5A patent/CN104953643B/zh active Active
- 2015-11-24 US US15/536,138 patent/US10110026B2/en active Active
- 2015-11-24 WO PCT/CN2015/095390 patent/WO2016180004A1/zh active Application Filing
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2533975A1 (en) * | 2005-01-31 | 2006-07-31 | Eaton Corporation | Wireless node and method of powering a wireless node employing ambient light to charge an energy store |
CN102157988A (zh) * | 2011-03-15 | 2011-08-17 | 东南大学 | 一种无线传感器网络节点的无线充供电方法 |
CN102355067A (zh) * | 2011-07-04 | 2012-02-15 | 东南大学 | 一种无线传感器网络节点的移动式无线充供电方法 |
CN202190128U (zh) * | 2011-07-04 | 2012-04-11 | 东南大学 | 一种无线传感器网络节点的移动式无线充供电装置 |
CN103219779A (zh) * | 2013-05-13 | 2013-07-24 | 东南大学 | 一种传感网节点无线充电方法 |
CN104953643A (zh) * | 2015-05-12 | 2015-09-30 | 合肥工业大学 | 一种多充电节点的无线传感器网络充电方法 |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114301084A (zh) * | 2022-01-11 | 2022-04-08 | 高振国 | 一种方向性无线充电车的传感网充电调度算法 |
Also Published As
Publication number | Publication date |
---|---|
CN104953643A (zh) | 2015-09-30 |
US10110026B2 (en) | 2018-10-23 |
CN104953643B (zh) | 2017-03-08 |
US20170353044A1 (en) | 2017-12-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2016180004A1 (zh) | 一种多充电节点的无线传感器网络充电方法 | |
CN108448731B (zh) | 一种协作式无线传感网能量补充方法及其无线传感网 | |
CN107835499A (zh) | 一种WSNs中基于分簇和能量中继的移动充电方法 | |
Ren et al. | Maximizing charging throughput in rechargeable sensor networks | |
Kumar et al. | Meta-heuristic range based node localization algorithm for wireless sensor networks | |
Hoang et al. | Realisation of a cluster‐based protocol using fuzzy C‐means algorithm for wireless sensor networks | |
CN109583665A (zh) | 一种无线传感器网络中的无人机充电任务调度方法 | |
CN204706925U (zh) | 基于bp神经网络的智能电池充电器 | |
CN110929464B (zh) | 一种基于改进蜻蜓算法的蓄电池参数辨识方法 | |
CN111757266A (zh) | 基于太阳能供电型农业物联网的uav数据采集轨迹算法 | |
Benmad et al. | Data collection in UAV-assisted wireless sensor networks powered by harvested energy | |
CN106209261B (zh) | 基于概率邻域网格的三维UASNs的移动数据收集方法 | |
Alsharif et al. | Notice of Retraction: Enabling Hardware Green Internet of Things: A review of Substantial Issues | |
CN110049500B (zh) | 基于模拟退火算法的无线可充电传感网中uav能量补偿方法 | |
CN103167578B (zh) | 用Hopfield神经网络对无线传感器网络分簇的方法 | |
CN109275170A (zh) | 一种无线可充电传感网络的充电方法及系统 | |
CN110248330B (zh) | 一种基于中继充电模型最大化充电小车休息时间调度方法 | |
Wang et al. | [Retracted] EMEECP‐IOT: Enhanced Multitier Energy‐Efficient Clustering Protocol Integrated with Internet of Things‐Based Secure Heterogeneous Wireless Sensor Network (HWSN) | |
Yang et al. | Power sensor networks by wireless energy—Current status and future trends | |
Ouadou et al. | Wireless charging using mobile robot for lifetime prolongation in sensor networks | |
CN106231636B (zh) | 基于概率邻域覆盖集的三维UASNs的移动数据收集方法 | |
Shen et al. | An ant colony system based energy prediction routing algorithms for wireless sensor networks | |
CN111224450A (zh) | 一种大规模无线传感网多位置同时充电方法 | |
CN107590976A (zh) | 用于大数据采集的无线传感器终端设备 | |
Li et al. | Multi-node energy policy for wireless sensor networks |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 15891700 Country of ref document: EP Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 15536138 Country of ref document: US |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 15891700 Country of ref document: EP Kind code of ref document: A1 |