How can i calculate five unknown parameters??

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Hello everyone,
I want to calculate the five unknown parameters for the following equations. Please could you give me a hint on how to do it?
Some of the parameters i already know them so i define them n = 1; k = 1.38064852 * 10^-23; T = 8; q = 1.60217662 * 10^-19; Vt = n*k*T/q; Np = 5; Ns = 12; Voc = 36.48; Isc = 8.12; Im = 7.62; Vm = 29.47;
These are the unknown parameters i am looking for: (Iph I_o Vt Rs Rp)
These are the equations i have and i want to solve them 1) Vt = (n*k*T)/q; 2) Np*Iph - Np*I_o*exp((Voc/Ns*Vt) - 1) - (Np/Ns) * (Voc/Rp) = 0; 3) Isc == Np*Iph - Np*I_o*exp((Isc*Rs)/(Np*Vt) -1) - ((Isc*Rs)/Rp); 4) Im == Np*Iph - Np*I_o*exp((((Vm/Ns)+((Im/Np)*Rs))/Vt) - 1) - Np* (((Vm/Ns) + ((Im/Np)*Rs))/Rp); 5) (Im/Vm) == ((Np/Ns*Vt)*I_o*exp(((Vm + Im*((Ns/Np)*Rs))/(Ns*Vt)) + (1/(Ns*Np)*Rp))) / (1 + (Rs/Vt)*I_o*exp((Vm + (Im*(Ns*Np)*Rs))/(Ns*Vt)) + (Rs/Rp)); 6) (-(1/Rp)) == ((-(Np/Ns*Vt))*I_o*exp((Isc*(Ns/Np)*Rs)/(Ns*Vt)) - (1/(Ns*Np)*Rp)) / (1 + (Rs/Vt)*I_o*exp((Isc*(Ns/Np)*Rs)/(Ns*Vt)) + (Rs/Rp)), Iph);
Thanks in advance
Regards,
Charalampos

Accepted Answer

Star Strider
Star Strider on 16 Nov 2017
Edited: Star Strider on 16 Nov 2017
Use the Optimization Toolbox fsolve (link) function.
  8 Comments
Charalampos Ioannou
Charalampos Ioannou on 21 Nov 2017
Hello Star,
I want to ask you a question instead of using random values can i have something else which is gonna give me the standard values??
For example when i am using the algorithm above every time is giving me different values.
How can i fix this?
Star Strider
Star Strider on 21 Nov 2017
Nonlinear optimization algorithms can be sensitive to initial parameter estimates, if the function being optimized has a number of local minima, a flat response hypersurface, a hypersurface charaterised by ‘saddle points’ (in which a global minimum might not exist), or other problems. If you know approximately what the optimum parameter values should be, start with those.
Another option would be to use one of the Global Optimization Toolbox functions to see if you can find the global minimum with an algorithm that does not use a gradient-descent approach.

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More Answers (1)

Alex Sha
Alex Sha on 22 Dec 2019
There are multi-solutions for Charalampos's problem:
1:
iph: -12.4464463252524
io: -889977.402184639
n: -4891.45375599277
rp: -3.43888384438778
rs: 29.2716150287422
Vt: -3.37210182925269
2:
iph: -1.58509863749155
io: -25.8943258325875
n: -2509.22818093014
rp: -1.9797561075646
rs: 1.83150481082548
Vt: -1.72982785098611
3:
iph: -6.55480935306723
io: -431499.497847303
n: -4852.19727384217
rp: -6.49397053909992
rs: 22.7965518323771
Vt: -3.34503894327367

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