一种基于单片机控制的新型光伏电池 毕业论文外文翻译

附录A
Microprocessor-Controlled New Class of Optimal
Battery Chargers for Photovoltaic Applications
Abstract
A simple, fast and reliable technique for charging batteries by solar arrays is proposed. The operating point of a battery is carefully for cednear the maximum power point of solar cells under all environmental (e.g., insolation, temperature, degradation) conditions. Optimal operation of solar arrays is achieved using the V oltage-Based Maximum Power Point Tracking (VMPPT) technique and the charger operating point is continuously adjusted by changing the charging current. An optimal solar battery charger is designed, simulated and constructed. Experimental and the oretical results are presented and analyzed. The main advantages of the proposed solar battery charger as compared with conventional ones are shorter charge time and lower cost.
Index Terms—Charger, microprocessor, maximum power point tracking (MPPT), photovoltaic.
I.INTRODUCTION
The field of photovoltaic systems is quite broad with many stand-alone and grid-connected configurations. Applications of solar energy include water pumping , refrigeration and vaccine storage, air conditioning, light sources, electric vehicles ,PV power plants ,hybrid systems , military and space applications.
Reference[8]has divided photovoltaic applications into four categories: large-scale grid connected systems, small remote photovoltaic plants, low power stand-alone systems, and a combination of solar systems with other alternative energy sources. These categories may also be viewed in terms of load characteristics. There are three load types:a DC load, a “dead” AC load, and a “live” AC load(e.g.,a utility system).Most of these applications use batteries as backup energy systems and/or matchingdevices for balancing their energy flow during peak load or poor environmental conditions (e.g., low insolation, high temperature or high degradation).The main drawbacks of PV systems are high fabrication cost, low energy conversion efficiency, and nonlinear characteristics. For increasing conversion efficiency, many Maximum Power Point Tracking (MPPT) techniques have been proposed and implemented. They can be categorized as:
A)“Look-up table”methods [12],[13]—The nonlinear and time varying nature of solar cells and their great dependency on radiation and temperature levels as well as degradation(aging,dirt,snow) effects, make it difficult to record and store all possible system conditions.
B)“Perturbation and observation(P&O)”methods [14],[15] —Measured cell
characteristics (current, voltage and power)are employed along with an on-line search algorithm to compute the corresponding maximum power point which is dependent on insolation, temperature or degradation levels. Problems with this approach are undesirable measurement errors(especially for current)which strongly affect tracker accuracy.
C)“Computational” methods [2],[16]–[19]—The nonlinear V-I haracteristics of a solar panel are modeled using mathematical equations or numerical approximations, and maximum power points are computed for different load conditions as a function of cell open-circuit voltages or cell short-circuit currents. In the literature, many battery charging techniques are investigated and proposed[20]–[24].These methods use avariety of battery characteristics(voltage and temperature) to achieve a safe and fast charging process. However, two well-known charging methods employing photovoltaic sources are the constant current charging, and the direct connection of solar panel to battery and load(e.g., battery tied solar systems).In this paper, a simple and fast variable-current charging tech-nique, based on “computational” methods, is proposed for photovoltaic applications —where photovoltaic charger and battery are matched with respect to voltage and current. Online measurements of panel open-circuit voltage are used to detect the maximum power point of a solar panel. Battery charge rate is continuously adjusted such that the system operating point is forced near the detected maximum power point of solar panels. The oretical and experimental analyses are used to demonstrate the reliability and validity of the proposed technique.
II.MODELING OF PROPOSED FAST SOLAR
BATTERY CHARGER
Electrical models for solar panel, maximum power point tracker, battery and battery charger will be used to simulate the proposed solar charging technique.
A.Solar Panel Model
Using the equivalent circuit of solar cells(Fig.1),the radiation and temperature dependent V-I haracteristics of m parallel strings with n series cells per string is
00()sc sa sa s sa I i mI n
n V In R i mI m
λ-+=- （1） where is the cell short-circuit current(representing in solation level), is the reverse saturation current,is the series cell resistance and is a constant coefficient which depends on the cell material and the temperature T.
For the silicon solar panel(,)used for theoretical and experimental analyses of this paper[Table I, manufactured by the Iranian Optical Fiber Fabrication Co.(OFFC)],(1)can be written as at T=25
0.000051.767()0.00005
sc sa sa sa I i V In i -+=- （2） Equations(3a)and(3b)are evaluated for one OFFC panel at T=70 and T=-20, respectively. Computed and measured V-I as well as P-I characteristics for the OFFC
panel are shown in Fig.2 for two insolation levels. This figure illustrates the variations of cell maximum power points (e.g., maxima of P-I curves)with respect to insolation levels.
3.0050.000241.69()0.00024
sa sa sa i V In i -+=- (3a) 20830.000011.82()0.00001
sa sa sa i V In i -+=- (3b) Eqs.(2)and(3)along with Fig.2 depict the strong nonlinear dependency of the Maximum Power Point(MPP)with respect to insolation and temperature levels and justify for any high efficient PV system an accurate MPP tracker.B.V oltage-Based Maximum Power Point Tracking to determine operating points corresponding to maximum power for different insolation and temperature levels,(2)and(3) are commonly used[2],[17]to compute the partial derivative of
power with respect to cell voltage.Instead of finding the maximum via derivative,[18]and[19]employ numerical methods to show a linear dependency between “cell v oltages corresponding to maximum power ”and“ cell open circuit voltages”
MP v OC V M V = (4)
This equation characterizes the main idea of the V oltage-Based Maximum Power Point Tracking (VMPPT) technique. Is called the“voltage factor”and is equal to 0.74 for the OFFC silicon cells[18],[19].Equation(4)is plotted in Fig.3 together with the computed(almost linear)dependency of with respect to(shown by “+” signs ). C. Nonlinear Battery Model Most battery models ignore the presence of nonlinear electro chemical characteristics[27],[28].For the theoretical and experimental analyses of this paper, we propose a new nonlinear model for Ni-Cd batteries as shown in Fig.4. Measurements show linear variations of, and nonlinear characteristics of with respect to charge rate: （5）
where is the charging current and R , Cs and Co are parameter values at biasing current level. For one cell of the 7 Ah Ni-Cd battery used for theoretical and experimental analyzes of this paper, the constants of(5)are obtained from measured characteristics(Table II)at charge rates of,and C. Computed and measured battery characteristics are compared in Fig.5. D.The Proposed Solar Charger For the optimal solar charger,an appropriate combination of the MPPT algorithm and battery charging technique must be selected. For the tracker, the simple and reliable voltage-based MPPT technique is used requiring very few components for sensing the solar-panel, open-circuit voltage. For the charging technique, variable-current charging is selected. This will allow the tracker to continuously adjust battery-charging rate and force the system operating point near the maximum power point of solar panels. Other tracking 1232123()()()()()()())lin s bat so rs bat o lin s bat so cs bat o lin P bat po cp bat o nonlin p bat p bat p bat p R f I R K I I C f I C K I I C f I C K I I R f I K I K I K ==+-==+-==+-==++
techniques could also be used. However, they require more components(for sensing panel short-circuit current and/or simultaneous panel voltage and current measurements)resulting in lower overall efficiency.
III.SIMULATION OF PROPOSED SOLAR
BATTERY CHARGER
Simulink software and its facilities are used to model the proposed solar battery charger(Fig.6).We have created a block called“PV Source”to simulate the nonlinear V-I characteristics of one OFFC solar panel(2)employing cell short-circuit current as a measure of insolation level [Fig.6(b)].Saturation and delay functions are introduced to limit the fast response of the “controlled voltage source”and to improve convergence. The output of this block is the panel operating voltage.
To simulate voltage-based maximum power point tracking, a block called “VMPPT”is introduced[Fig.6(c)]that uses
and to generate desired duty cycles for the charge unit.
The panel open-circuit voltage is calculated,thereafter the panel voltage corresponding to maximum power(4)is computed and compared with and the error is amplified through a proper transfer function to generate the desired duty cycle.
The charger unit consists of a DC/DC buck converter
(chopper and output filter)and a LC input filter. The chopper includes a fast switch and a schottky diode. A block called“B attery Parameter Calculation”computes battery parameters [Fig.4 and(5)]corresponding to the system operating point.
IV.CONSTRUCTION OF PROPOSED SOLAR
BATTERY CHARGER
Fig.7 shows the constructed battery charger, which consists of the following parts:
Silicon Solar Panel—one OFFC silicon solar panel with maximum output power of about 35 W(Table I)is used togenerate solar energy. Microprocessor—The 8085 Micro Controller Unit(MCU)is used to record and process measured voltage and current waveforms and to compute required signalsfor control and drive circuits. The 1524 IC employed to generate the required PWM command(e.g.,at 50 kHz)and voltage/current signals for the charger unit. Thevoltage-based MPPT for the solar panel is implemented by MCU under different environmental and output operating conditions. Note that the panel open-circuit voltage is continuously measured at a slower rate (e.g., every minute).Fig.8 shows the main functions of the MCU. If multiple solar panels with similar characteristics are used, a reference panel could be relied on to sense the open-circuit voltage. Any shadowing effects caused by dust, snow or clouds will result in power-current characteristics with several maxima. This will complicate MPPT.
Charger Unit—A chopper circuit is used to properlyconnect and
disconnect—based on PWM signals—solarpanel from battery and load. Input and output filters are employed to suppress electrical noise at the output of the solar panel and at the input of the battery.Input and output current and voltage sensors are relied on for signal measurements.
Battery and Load—Five units of 7 Ah Ni-Cd batteriesare connected in series to store electrical energy. Resistors serve as loads during discharging and charging modes, respectively. In discharge mode, the solar panel is partially or totally inactivated by shadow or eclipse effects.
V.ANALYSIS OF EXPERIMENTAL AND
THEORETICAL RESULTS
Three charging methods are investigated: the proposed variable-current charging (method 1), direct connection of battery and load to solar panel(method 2),and constant-current charging(method 3). Battery (full) charging state is detected using the approach (e.g., using magnitude and slope of battery voltage as a function of time)of[24].
Experiments are performed for the following three operating conditions.
Case A:Operation at an Incidence Angle of about Measured and computed time functions for battery current and voltage as well as solar panel power and voltage are shown in Fig.9 for normal operating condition(e.g.,normal insolation and temperature).As expected,fine tracking of solar maximum output power is achieved throughout the charging process when the proposed charging technique is used[Fig.9(c)],method 1).Charging time for the proposed method is only 3 hours which is about 73%and 52%of the required charging times for methods 2 and 3,respectively. In method 1,panel voltage(corresponding to maximum power)which is determined by(4)is slightly higher at 11 A.M.due to lower environmental temperature.In method 2,panel voltage[e.g.,in Fig.9(d)]and its operating point is dominated by battery voltage.This causes panel output power to decrease from 29 W(for method 1)to about 20 W(for method 2).In method 3,panel voltage[about 17 V in Fig.9(d)]is determined by panel current which is proportional to the constant battery current (e.g.,0.2 C).This rate of charge is used to determine panel operating points for the simulation as outlined in Fig.6.The comparison of computed(X)and measured results forsome selected operating points is shown in Fig.9.
Case B:Operation at an Incidence Angle of about Similar experiments are performed for a change in angle of incidence(Fig.10).At 12:30 P.M.the solar panel is rotated forward(in the direction of sun)such that the angle of incidence is changed from about to about. During the first 105 minutes, the charging processes of the three methods are normal and results are similar to Fig.9. At the start of changing the angle of incidence from about to about, maximum panel output power is decreased to about 25 W[Fig.10(c),method 1].Our detailed measurements show that under all operating conditions (e.g., before and after changing the angle of incidence),method 1 continues to adjust panel operating point near the maximum power point of the V-I characteristics. The angle of incidence of about increases charge time of method 1 to
about 3.2 h. Methods 2 and 3 are not able to completely charge the battery since their operating points are not optimally selected. Note the inherent small voltage regulation of method 1,caused by the increasing slope of battery voltage. This is not true for methods 2 and 3 where fast voltage drops [e.g., at 12:30 P.M. and 13:45 P.M.in Fig.10(b)]occur. The measured characteristics of method 3 are interesting: constant-current charging continues for some time after changing the angle of incidence from to,this is so because the battery requires about 20 W of power [Fig.9(c),method 3].At 13:45 P.M.,the solar panel is no longer able to produce the required power since its maximum power is decreased to about 20 W. The converter duty cycle is forced to unity, causing direct connection of panel, battery and load. Therefore, measured characteristics of methods 2 and 3 become similar.
Case C: Operation with Eclipse This environmental operating condition is essential in satellite and spacecraft applications .Cease of insolation along with considerable temperature drop makes panel V-I characteristics very different before and after eclipse. We have generated this effect(Fig.11)by completely covering solar panel from 12:00 to 12:30 P.M. and decreasing its temperature from 24 C to 12 C As expected, charge time of proposed method is slightly increased to 2.8 h which is about 65%and 63%of the times required for methods 2 and 3,respectively. Note the increased panel maximum output power from 28 W(before eclipse)to 33 W(just after eclipse)due to temperature effects(Fig.11).The temperature drop does not change panel output power in method 2 because the panel operating point is dominated by the constant battery voltage. Similar analysis holds for method 3 where the panel operating point is mainly determined by constant panel current, caused by the constant battery current. Note that the stored energy in the battery[e.g.,] is not exactly equal for the three charging methods(Table III).This is due to different charging currents, which changes battery charging efficiency[29]
VI.CONCLUSIONS
V oltage-based maximum power point tracking and a nonlinear battery model are used to introduce a new class of microprocessor based optimal solar battery chargers.
A photovoltaic system consisting of a silicon solar panel, charger unit,Ni-Cd batteries and a resistive load is constructed and simulated. Based on theoretical and experimental results which are performed for the proposed charging technique(method 1),the direct connection of solar panel to battery and load(method 2),and the constant current charging(method 3),the following conclusions are drawn:
Computed results for selected operating points show good agreements with measurements.
Under different operating conditions, the solar panel output powers are larger for the proposed charging technique(method 1)as compared to methods 2 and 3(e.g., 20%to 65%).Therefore, the proposed charging technique requires fewer solar panels(e.g., lower cost).
The proposed charging technique is faster than methods 2 and 3(e.g.,40%to 75%shorter charging times)under different environmental conditions. Under low insolation condition(e.g., angle of incidence of about),charging time of proposed
technique is increased by 20%while methods 2 and 3 fail to charge the battery since their operating points on panel V-I characteristics are not optimally selected.
The battery stored energy for the proposed charger is less as compared to methods 2 and 3 due to the dependency of charging efficiency on the charge current[29]. The proposed charging technique does not introduce rapid voltage drops and establishes an inherent small voltage regulation, especially under unfavorable environmental conditions. Therefore, the proposed charging technique is suggested to replace unregulated photovoltaic systems.
附录B
一种基于单片机控制的新型光伏电池
摘要
本文提出了一种简单、快速可靠的太阳能电池阵列技术，使光伏电池在各种环境下（例如日照、温度等）都能接近最大功率点，理想的太阳能电池阵列工作点是通过基于最大功率点追踪技术（VMPPT）和控制工作点持续调节对改变的控制流改变来实现的。

一种理想的太阳能电池控制是可以被实现、仿真和计算的。

试验和理论分析的结果已经证明了这一点。

本文所提出的太阳能电池控制技术和传统的太阳能电池控制技术相比最主要的特点是缩短了控制时间，降低了成本。

关键词：控制，微处理器，最大功率跟踪（MPPT），光伏发电
1.说明
光伏系统的领域包括许多独立的和并网的结构，范围十分广阔。

太阳能的应用例如抽水机、冷藏和接种疫苗存储、空调、光能、电力交通，电池板，混合系统以及太空应用。

光伏应用通过参考可被分为四类：大功率并网系统，小功率的远程代养能电池板，低功率独立系统以及太阳能系统和其他能源替代物的混合。

这些种类同样可以被认为是各种形式的负载特性曲线。

共有三种类型：直流负载，交流接地负载和交流接高电平负载。

这些电池应用大部分被作为能源系统的备份或者一些平衡装置为了平衡其他能源在负载最大值或者恶劣条件下流动（例如低光强，高温等）
电压功率特性系统最主要的缺点就是高成本、低转化效率和非线性特性。

为了提高转化效率，许多的最大功率点跟踪技术已经被提出和实现。

他们可以被分类为以下几种：
A）查表法—太阳电池非线性和时间变化特性以及他们在辐射和温度还有降低（例如灰尘、冰雪等）的相关性，增加了对环境系统的记录和存储的难度。

B）微量变化观察法—测定的电池特性（电流、电压和功率）被变化为线性的算法，然后在基于光强、温度和降低确定的基础上计算出相应的最大功率点。

这种方法的问题在于在跟踪准确度要求很高的时候会出现很多不可预测的错误。

C）计算法—太阳电池板的电压和电流非线性特性通过数学方程或者近似数值进行仿真，最大功率点可以计算出在不同负载情况下的特性，比如说电池开路或者电流短路时的情况
在文献中，许多的电池控制技术被研究和提出。

这些方法运用各种电池特性（电压和温度）来实现一种安全的、快速的控制过程。

然而，使用光伏电源的两个最著名的控制方法是电流连续控制法和太阳板电池和负载直接连接法。

在本文中，控制通过计算法研究和提出的一种真对光伏应用的简单快速的控制方法，使光伏电池和控制与电压和电流相互匹配。

在线测量电池开路情况来检测太阳能电池板的最大功率点。

理论分析和实验证明：本文所提出的技术的可
靠性和合理性是正确的。

2. 太阳电池快速控制模型
太阳电池板电路模型，最大跟踪功率点，电池和电池控制在太阳能控制技术中将会被进行仿真。

A.太阳电池板模型
通过和太阳能电池等价的电路模型，m 个平行电池板，每个电池板n 个电池的光强和温度V-I 特性如下式： 00()sc sa sa s sa I i mI n
n V In R i mI m
λ-+=- （1）
图1 太阳电池的等价电路
其中Isc 是电池短路电流，Io 是反向饱和电流，Rs 是输入电阻，r 是和电池材料以及温度T 有关的连续性参数。

本论文使用的是硅晶体进行理论和试验分析。

其中（标准情况下m=1，n=36，T=25C ）
0.000051.767()0.00005
sc sa sa sa I i V In i -+=- (2) 这里同时还存在和温度的非线性关系。

考虑到温度变化对仿真的影响，在确定光强的基础上，对不同温度将会得到得出的不同系数。

3.0050.000241.69()0.00024
sa sa sa i V In i -+=- (3a) 20830.000011.82()0.00001
sa sa sa i V In i -+=- (3b) 方程3a 和3b 在一个标准电池板且T=70以及T=-20时各自进行估算。

在标准情况下，当光蔷薇不同值时，通过2式计算测量出的V-I 和P-I 特性曲线如图2所示。

这个图标说明电池最大功率点随着光强的变动而变化。

方程2和3还有图2描绘了在不同光强和不同温度下最大功率点的非线性特性，这个特性适用于任何电压功率系统以及最大跟踪功率点计算中。

B.基于最大跟踪功率点的电压
为了确定在不停光强和温度下相应的电池工作点，（2）和（3）通过用来计算不同电池电压相应功率的偏导数。

不同于找到最大导数值，【18】和【19】通过数字方法显示了在电池最大功率时的电压以及电源开路电压之间的线性特性。

MP v OC V M V = (4)
这个方程描述了基于最大跟踪功率点（VMPPT ）技术的基本情况。

Mv 是电压因子，其值在标准条件下为0.74。

图3说明了方程（4）计算出在Vmp 和相应的Voc 之间的关系（接近直线）。

C.电池非线性模型
大部分的电池模型忽略了电池特性中非线性的特点。

在本文的理论分析和试验中，我们提出了一种新的基于Ni-Cd 电池的非线性模型。

测量说明了Rs Cs Cp 的线性变动以及Rp 的非线性特性：
1232123()()
()()
()()
())lin s bat so rs bat o lin s bat so cs bat o lin P bat po cp bat o nonlin p bat p bat p bat p R f I R K I I C f I C K I I C f I C K I I R f I K I K I K ==+-==+-==+-==++ (5)
其中Ibat=Ic 是主控制电流，Rso Cso 和Cpo 是基于偏执电流Io 的相关参数。

本文在分析和实验时使用7Ah 的Ni-Cd 电池。

公式（5）中的常数是在变化率分别为0.5C 0.75C 和C 情况下测量得到的。

D.太阳能控制
对于理想的太阳能控制，必须选择一个MPPT 算法和电池控制技术适当结合的技术。

对于跟踪器来说，一个简单稳定的基于电压的MPPT 技术只需要很少的元器件就能实现太阳能板的灵敏度和开路电压。

对于控制技术来说，选择变化的电流控制。

这就要求跟踪器不断地去适应电池控制的平率并且强制系统的工作点尽量接近太阳能电池板的最大功率点。

也可以使用其他的跟踪技术。

但是其他的技术会要求更多的元器件（对于电池板短路电流的灵敏度或者对电池板电压和电流测量的仿真），这就导致系统的转化效率会降低。

3. 太阳能电池控制的仿真
我们制作了一个PV 源模块，用来仿真在标准情况下电池板电流短路情况下的V-I 非线性特性曲线，用来测量光强对太阳能电池的影响。

引入饱和以及延迟功能来限制电压控制源的快速反应，来提高密集性。

这个模块的输出就是电池板的工作电压。

为了仿真基于电压变化下的最大功率跟踪点，我们提出了“VMPPT ”控制模块，用电流Isc 和电压Vsa 来产生循环使用的控制模块。

通过计算电池板的开路电压，而后电池板的开路电压对计算出的最大功率进行相应的调整，和Vsa 相比较，通过一个适当的传输功能，误差被放大，进而得到了期望的循环工作。

控制单元由一个DC/DC 转化模块和一个LC 输入滤波组成。

芯片包括一个快速开关和一个二极管。

电池参数计算模块计算出了在系统工作点下的电池参数。

4. 太阳能电池的控制结构
电池板的控制结构由以下几部分组成：
硅太阳能电池板—一个标准的硅太阳能电池板在产生太阳能是最大的输出功率是35W 。

微控制器 -----本系统用8085单片机芯片来记录和控制被测电压和电流波形，然后产生需要的信号，来控制和驱动电路。

1524 IC 芯片用来产生控制单元的PWM 调制命令和电压/电流信号。

太阳能电池的基于电压的MPPT 技术在不同的环境和输出工作环境下通过单片机被执行。

电池板的开路电压在一个较低的频率下，继续记录其变化。

单片机最主要的功能如图8所示。

如果使用多组电池板进行仿真，一个附加的电池板可以用来控制开路电压灵敏度。

任何通过灰尘、雪或
者云所产生的阴影效果将会被记录在电流和功率特性曲线中，这将增加MPPT控制技术的复杂性。

控制单元—一个芯片电路来实现基于PWM信号以及来自太阳能电池板和负载的相互之间的连接和断开。

输入和输出滤波器用来消除太阳能输出和电池输入的电子噪声。

通过信号的测量来实现电流和电压输入和输出的检测。

电池和负载—五组7Ah的Ni-Cd电池连接在一起来（Vbattery=5（1.5）=7V）存储电能量。

尤其是在释放和控制模块中电阻可以用来作为负载，在非控制模块，太能电池板在日落时部分或者全部电池板将不再进行追踪。

5.试验和理论结果分析
以上提出的三种控制方法：电流变量控制法，电池和太阳能负载直接连接控制法和电流连续控制法。

电池控制模块用-At来检测。

在以下三种工作环境下进行了试验：
A：同太阳能电池板工作在正常的条件下一样，测量和计算电池电流和电压的时间功能。

按如期值来讲，对太阳最大输出功率跟踪的实现是党所使用的控制技术改变时对处理过程也进行控制和改变。

在上述方法中处理时间的控制仅仅是在方法2和3的所需控制时间的73%和52%。

在方法1中，电池板的电压在上午11：00微小的升高时有很低的环境温度所决定的。

在方法2中，电池电压和他的工作点由电池电压所支配。

这就引起了电池板输出功率从29W减小到大约20W。

在方法3中，电池电压由何连吃的电池电流成比例的板子的电流所决定。

这种控制速率被用在决定电池板在仿真模式下的工作点的确定。

计算和测量的结果的工作点在图9中进行了对比。

B：工作在a=40的角度下
仿真实验在角度反生变化时进行的。

在12：30时太阳板从0旋转到40度。

在刚开始的105分钟内，三种方法的控制进程是相同的，而且结果是相似的。

在从0到40度开始转化时，最大的电池板的输出功率开始从25W减小。

我们详细的实验结果表明在所有的工作条件下，方法1能持续适应电池板的各种在最大功率点时的工作条件。

在40度时方法1和控制时间开始增长，但是方法2和3不能完全地控制电池，如果工作点不是在理想情况时。

记录方法1内部的小的电压的规律，由电池电压小的倾斜的曾江所造成的。

这在方法2和3中是不可能实现的。

这种方法3的测量测性是很有趣的：连续的电流控制在一段时间内，在角度从0变到40以后，这时因为电池需要大约20W 的功率。

在下午13：45时，太阳板不再按要求的功率产生电流，功率也降到了20W。

通过转换器的使用，和电池板，电池和负载直接相连。

因此，方法2和3的测量测性是相似的。

C：工作在日食下
这个试验的工作条件在卫星和太空应用中是至关重要的。

光强伴着巨大的温度较低时电池板的V-I特性在停止前和停止后完全不同。

我们通过在12：00到12：30遮盖光线的试验证明了温度从24降到了12度
正如所预料的那样，控制时间是微量变化的，大概65%到63%的时间在方法2和3中产生了这种情况。

记录电池板产生的功率从28升高到33w取决于温度的作用，如图11所示。

这种温度降落在方法2中不能改变电池板的输出功率，因为电池板的工作点由持续的电池电压所决定的。

相同的情况在方法3中也是一样的。

记录所存在的电池能在三种方法中结果不是十分相同的，这时由于不同的控制电流所决定的。

6.结论
基于最大功率跟踪点的电压和非线性的电池模型的使用，本文引出了一种新的单片机的控制方法。

一个太阳能系统由太阳能硅板，控制系统和Ni-Cd电池和各种负载所组成的。

通过在直接控制技术（方法1），直接电池负载连接法（方法2）和持续电流变化法（方法3）的理论分析和实现，得出如下结论：计算所得到的工作点和测量所得到的工作点是相吻合的
在不同的工作条件下，太阳能板输出功率在方法1中和方法2和3相比，要大很多。

因此，所提出的控制技术需要很少的太阳能板（低成本）所提出的控制技术在不同的工作环境和条件下比方法2和3速度快，效率高在低光照下，所提出技术的控制时间增大20%到30%，而方法2和3无法实现在低光照下运行
电池存储在所提出的方法中和方法2和3相比，对控制电流的依赖程度更低。

所提出的控制技术不能引进电压快速降落以及内部电压很小时情况的实现，尤其是在环境条件很不利时。

因此，所提出的方法还有待改进，进一步适应和替代非校准的光伏系统。