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TPS73701DRVEVM-529: Minimizing current in the resistor divider network

Part Number: TPS73701DRVEVM-529

Hi Team,

We are using TPS73701 Adjustable LDO in a battery powered design. When the device is in deep sleep mode, we observed that the voltage divider network is consuming more than 100uA of current with the resistor divider combination of 51.1K & 30.9K. This is the recommended value given in the datasheet where in the datasheet recommends the parallel combination of the resistor network to be equal to 19K for best accuracy.

We are planning to increase the resistor value such that the current consumption is the least. However if we do this we will not be able to maintain 19K parallel combination. How would this affect the accuracy of the LDO. Could you please recommend the resistor divider combination which suits our requirement.

Kindly provide your suggestions.  

Below attached the recommended resistor values for the resistor divider network.

  

  • Hi Anand,

    The datasheet recommendation is to allow the customer to easily ignore the nonideal feedback current, which adds an error term to the Vout equation you see in your image from the datasheet.  We can run statistical analysis software to assess the tolerance when you need to increase the feedback resistors to lower the quiescent current, as you are describing.  Please provide me your Vout and the Vout steady state tolerance, and I will run the statistical software to give you your best resistor combinations.

    Thanks,

    - Stephen

  • Hi Stephen,

    Appreciate your quick response,

    Kindly consider the Vout = 3.2V and steady state tolerance of 1%.

  • Hi Anand,

    Keep in mind that the internal reference error is at best +/- 1% but only at room temperature.  The addition of the external feedback resistors will always lead to a slight increase in the tolerance. 

    I ran 100,000 monte carlo simulations for every resistor combination from 100 k-ohms to 10 megaohms using E196 series resistors.  Each resistor is 0.1% tolerance.

    While the reference voltage and resistors are typically +/- 6 sigma, most customers do not have the manufacturing volumes to require this in their specifications.  +/- 6 sigma inside a tolerance spec of +/- 1% is more costly than +/- 3 sigma inside the same tolerance spec.  A more common requirement is +/- 3 sigma which is 99.7% of all production units passing.  So individual parameters are modeled as +/- 6 sigma but I recommend using +/- 3 sigma for your Vout requirement.

    Unfortunately the feedback current is probably too high to choose very large R1/R2 feedback resistors.  The error caused by this current begins to dominate the output voltage at large R1/R2 values.  If these results are insufficient then what you need is a different LDO with smaller feedback current.

    R1 R2 Vout Average Vout Standard Deviation
    294000 102000 3.194082499 0.015196783
    301000 105000 3.183633327 0.015561881
    309000 107000 3.202980518 0.015930766
    316000 110000 3.192981958 0.016275166
    324000 113000 3.191005468 0.016685644
    332000 115000 3.209165335 0.017052786
    340000 118000 3.207084894 0.017407628
    348000 121000 3.205226421 0.017867167
    357000 124000 3.210325956 0.018263122
    365000 127000 3.208712578 0.01872226
    374000 130000 3.213738441 0.019053021
    383000 133000 3.218659401 0.019528423
    392000 137000 3.206651211 0.019967744
    402000 140000 3.21774292 0.020478455
    412000 143000 3.228495121 0.021009073
    422000 150000 3.177266598 0.02135295
    432000 154000 3.173755884 0.022007652
    442000 154000 3.228703976 0.022506421
    453000 162000 3.172937155 0.022899138
    464000 165000 3.188897133 0.023483854
    475000 169000 3.191020727 0.024000872
    487000 174000 3.185180426 0.024586387
    499000 178000 3.192396641 0.025229147
    511000 182000 3.199453831 0.025833756
    523000 187000 3.194333315 0.026427049
    536000 191000 3.205826283 0.026948541
    549000 196000 3.205516338 0.027574243
    562000 200000 3.216599941 0.028359856
    576000 205000 3.220604897 0.029157942
    590000 210000 3.22461915 0.029735759
    604000 215000 3.228641987 0.030418839
    619000 226000 3.176850557 0.031196158
    634000 232000 3.17640686 0.031972848
    649000 237000 3.185417414 0.032544564
    665000 243000 3.188800573 0.033529375
    681000 249000 3.192251921 0.034292866
    698000 255000 3.199203968 0.035037193
    715000 261000 3.2060709 0.035812173
    732000 267000 3.212858438 0.036880206
    750000 274000 3.214781046 0.037589006
    768000 280000 3.224685669 0.038767744
    787000 294000 3.177596569 0.039483782
    806000 301000 3.183992624 0.040665053
    825000 309000 3.183422327 0.041394502
    845000 316000 3.19274044 0.042500459
    866000 324000 3.198071718 0.04351867
    887000 332000 3.203449488 0.04464791
    909000 340000 3.211523533 0.04551661
    931000 348000 3.219529867 0.046712801
    953000 357000 3.221474171 0.047908295
    976000 374000 3.180500507 0.049010098
    1000000 383000 3.188772917 0.049961444
    1020000 392000 3.187632799 0.050968785
    1050000 402000 3.204552412 0.052633446
    1070000 412000 3.19866991 0.053595711
    1100000 422000 3.215308189 0.055145711
    1130000 442000 3.184248924 0.056784514
    1150000 453000 3.175905228 0.057503417
    1180000 464000 3.188482761 0.058936313
    1210000 475000 3.200894833 0.060521662
    1240000 487000 3.20896101 0.062035825
    1270000 499000 3.217072248 0.063610405
    1300000 523000 3.178527832 0.065288812
    1330000 536000 3.18407464 0.066195689
    1370000 549000 3.207357168 0.068950571
    1400000 562000 3.212882519 0.07038945
    1430000 576000 3.215111256 0.071838245
    1470000 604000 3.188019991 0.073868811
    1500000 619000 3.188610792 0.075180061
    1540000 634000 3.205217838 0.077172875
    1580000 649000 3.221611738 0.079174012
    1620000 681000 3.189083815 0.081254937
    1650000 698000 3.186117649 0.082304433
    1690000 715000 3.197909117 0.084430888
    1740000 750000 3.177999973 0.087266214
    1780000 768000 3.188166618 0.0890866
    1820000 787000 3.196063519 0.091286078
    1870000 806000 3.217079401 0.093772866
    1910000 845000 3.181284189 0.095490441
    1960000 866000 3.198623657 0.098216422
    3830000 2430000 3.209905386 0.099615976
    3920000 2550000 3.20580411 0.099653848
    4420000 3320000 3.191060305 0.099739254
    5620000 6340000 3.19514823 0.099803224
    4990000 4420000 3.200167418 0.099823475
    2430000 1150000 3.219434738 0.099869654
    3160000 1740000 3.200873613 0.099878259
    4870000 4120000 3.206631184 0.099883623
    3320000 1910000 3.18657589 0.099904448
    4320000 3160000 3.18967104 0.099910282
    4120000 2800000 3.213142872 0.099911422
    5230000 4990000 3.207477093 0.099924311
    2150000 976000 3.207295179 0.09993799
    3090000 1690000 3.189722061 0.099942006
    3480000 2050000 3.202048779 0.099965543
    2870000 1500000 3.191666842 0.099966526
    3010000 1620000 3.189419746 0.099990927
    6040000 8250000 3.197697163 0.099993318
    2610000 1300000 3.18915391 0.10001301
    2740000 1400000 3.187714338 0.100029893
    2940000 1540000 3.209272861 0.10003271
    3740000 2320000 3.21165514 0.100050174
    2670000 1330000 3.207015038 0.100062862
    2370000 1130000 3.188876152 0.100064822
    2050000 909000 3.219180584 0.100065656
    5490000 5900000 3.191406965 0.100073859
    4530000 3480000 3.200379372 0.100126058
    2800000 1430000 3.206433535 0.100129806
    5760000 6810000 3.204652071 0.100136355
    2490000 1210000 3.193281174 0.100147732
    3240000 1820000 3.196175814 0.100170247
    3570000 2150000 3.199372053 0.100178972
    2210000 1020000 3.196333408 0.100183129
    3650000 2260000 3.187035561 0.100185595
    4020000 2670000 3.210494518 0.100194007
    2550000 1240000 3.210161448 0.100209162
    5900000 7500000 3.199333429 0.100209691
    2320000 1100000 3.183272839 0.100215577
    6190000 9090000 3.201774597 0.10023462
    4750000 3920000 3.194387913 0.100239269
    4220000 3010000 3.187594652 0.100247137
    2100000 953000 3.192854166 0.100249559
    2260000 1050000 3.199904919 0.100277737
    4640000 3650000 3.208986282 0.100322694
    3400000 1960000 3.207755089 0.100327969
    2000000 887000 3.203833103 0.100356594
    5110000 4750000 3.193631649 0.10036812
    5360000 5360000 3.208000183 0.100383297

    Thanks,

    - Stephen

  • Hi Stephen,

    Thank you for your response.

    Our output voltage is 3.2V and we may have up-to 3% tolerance.

    Could you please give us more details on how you have tabulated these resistor values.

    For Ex, considering R1 and R2 to be 301k and 105k, we are observing around 3.48V output voltage in our board(Higher than the required 3.2V). But the simulated value provided in the table (previous response) it is around 3.2V.

    The output voltage equation given in the datasheet : VOUT = (R1 + R2)/R2 ´ 1.204. However, with the given values(for ex: 301k and 105k), Vout tends to be greater i.e around 4.6V(which is not feasible in our case, as input is around 3.7V). 

    Kindly share your thoughts regarding the same. 

    Also, could you please let us know the quiescent current of the IC

    Thank you.

  • Hi Sushruta,

    I have received your reply and I need up to 2 business days to provide a response.  But yes, I can go into as much detail on this topic as you would like.  Please give me some additional time to provide a response and we will go from there.

    Thanks,

    - Stephen

  • Thank you Stephen.

    We will be waiting for your response.

    Warm Regards,

    Sushruta

  • Thank you for you patience Sushruta. 

    Best,

    Juliette

  • Hi Sushruta,

    Thank you for your patience.   I went back and reviewed the simulation, and there is a typo in the value for Vref.  I apologize for this mistake, please find the updated table below.

    The simulation is run using a 100,000 monte carlo simulation for each R1/R2 pair.  Vref is 1% tolerance from the datasheet, the feedback pin current is taken from the datasheet with a maximum of 600 nA, and R1 and R2 are assumed to be 0.1% tolerance and are chosen from standard E96 series resistors.  I assume 6 sigma's in for all manufacturer tolerances.

    R1 R2 Vout Average Vout Standard Deviation
    162000 100000 3.203079939 0.009651814
    165000 102000 3.201147079 0.00974962
    169000 105000 3.192566633 0.009928565
    174000 107000 3.21410656 0.010156969
    178000 110000 3.205690861 0.010360661
    182000 113000 3.197785854 0.010534638
    187000 115000 3.217908621 0.010707692
    191000 118000 3.210147381 0.010907338
    196000 121000 3.213080883 0.011153105
    200000 124000 3.205935478 0.011293004
    205000 127000 3.208964586 0.011529266
    210000 130000 3.211923122 0.011702999
    215000 133000 3.214815855 0.011934763
    221000 137000 3.21251893 0.012249774
    226000 140000 3.215399981 0.012433426
    232000 143000 3.226942539 0.012742744
    237000 147000 3.21624279 0.012969529
    243000 154000 3.176718235 0.013237286
    249000 158000 3.176142931 0.013460996
    255000 158000 3.223664522 0.01381425
    261000 165000 3.186809063 0.01409185
    267000 169000 3.18627739 0.014333727
    274000 174000 3.18215394 0.014610843
    280000 178000 3.181932688 0.014912781
    287000 182000 3.188715458 0.015284868
    294000 187000 3.185119867 0.015576725
    301000 191000 3.191703081 0.015901368
    309000 196000 3.194842815 0.016342834
    316000 200000 3.2011199 0.016609533
    324000 205000 3.204107285 0.016966896
    332000 210000 3.207066774 0.01741232
    340000 215000 3.210000038 0.017786711
    348000 221000 3.204291344 0.018142182
    357000 226000 3.21299386 0.018549467
    365000 232000 3.207724094 0.018991202
    374000 237000 3.216183186 0.019348131
    383000 243000 3.21656251 0.019855408
    392000 249000 3.21705389 0.020317592
    402000 261000 3.179036856 0.020763056
    412000 267000 3.185457706 0.021204032
    422000 274000 3.184935808 0.021748109
    432000 280000 3.191200018 0.022192307
    442000 287000 3.190843821 0.022511851
    453000 294000 3.195042849 0.023280177
    464000 301000 3.199199915 0.023782054
    475000 309000 3.197309017 0.024316728
    487000 316000 3.205631733 0.024844091
    499000 324000 3.208008528 0.025335461
    511000 332000 3.210444689 0.026021123
    523000 340000 3.212935209 0.026645422
    536000 348000 3.219236851 0.027245872
    549000 357000 3.220229387 0.027976226
    562000 374000 3.181819201 0.02851533
    576000 383000 3.187515497 0.02926795
    590000 392000 3.193142891 0.029841511
    604000 402000 3.194195032 0.03058574
    619000 412000 3.198622227 0.03136022
    634000 422000 3.203052998 0.032128982
    649000 432000 3.207487106 0.032793906
    665000 442000 3.214947939 0.033586722
    681000 453000 3.218286753 0.034396421
    698000 475000 3.182646275 0.035332657
    715000 487000 3.186179638 0.035874285
    732000 499000 3.189788342 0.036804855
    750000 511000 3.196123362 0.037834454
    768000 523000 3.202415228 0.038648278
    787000 536000 3.207913399 0.039688688
    806000 549000 3.213421106 0.040651303
    825000 562000 3.218937635 0.041393638
    845000 590000 3.181872845 0.042588819
    866000 604000 3.190064907 0.043514434
    887000 619000 3.195379496 0.044698637
    909000 634000 3.202939749 0.045687623
    931000 649000 3.210455656 0.046601474
    953000 665000 3.215331554 0.047687463
    976000 698000 3.180330038 0.049078364
    1000000 715000 3.18791604 0.05031551
    1020000 732000 3.187704802 0.051122397
    1050000 750000 3.204600096 0.052763283
    1070000 768000 3.202447891 0.053723618
    1100000 787000 3.216846228 0.055051908
    1130000 825000 3.192115068 0.056664258
    1150000 845000 3.18757987 0.057455052
    1180000 866000 3.198554277 0.059084393
    1210000 887000 3.209435225 0.060544595
    1240000 909000 3.218420267 0.062208042
    1270000 953000 3.189491034 0.063946508
    1300000 976000 3.19768858 0.06530562
    1330000 1000000 3.204319954 0.066771671
    1370000 1050000 3.185933352 0.068542518
    1400000 1070000 3.199326992 0.07027147
    1430000 1100000 3.198199987 0.071504608
    1470000 1130000 3.211265564 0.073644675
    1500000 1180000 3.184508562 0.075061463
    1540000 1210000 3.198363543 0.076819293
    1580000 1240000 3.212129116 0.079207361
    1620000 1300000 3.190369129 0.080900922
    1650000 1330000 3.192684174 0.082288064
    1690000 1370000 3.196226358 0.084606141
    1740000 1430000 3.191006899 0.086905345
    1780000 1470000 3.195904732 0.089244574
    1820000 1500000 3.210853338 0.091691211
    1870000 1580000 3.189987421 0.0935385
    1910000 1620000 3.196530819 0.095297612
    1960000 1690000 3.188354969 0.097801134
    3480000 4420000 3.19594574 0.099539816
    2050000 1780000 3.20562911 0.099560298
    3090000 3480000 3.200068951 0.0996539
    2670000 2670000 3.209000111 0.099805161
    2800000 2940000 3.190666676 0.099805355
    3830000 5490000 3.192949057 0.099813923
    3570000 4640000 3.20135355 0.099819273
    2320000 2150000 3.199199915 0.09982051
    3320000 4020000 3.194348335 0.099844508
    4220000 6980000 3.197919846 0.099876992
    2100000 1870000 3.186085463 0.099892989
    3160000 3650000 3.19436717 0.099958502
    3400000 4220000 3.194047451 0.099976987
    4640000 9310000 3.196060181 0.099989749
    2150000 1910000 3.204288006 0.100012131
    4530000 8660000 3.192806005 0.100050092
    2550000 2490000 3.202012062 0.100062795
    2610000 2610000 3.190999985 0.10010691
    2370000 2210000 3.206167459 0.10011334
    4420000 7870000 3.206198215 0.100155942
    2210000 2000000 3.19742012 0.10017892
    3650000 4870000 3.201381922 0.100189164
    4320000 7500000 3.193504095 0.10020671
    4120000 6490000 3.20432663 0.100230835
    2000000 1740000 3.187908173 0.100233108
    2490000 2430000 3.184728384 0.100267977
    3740000 5110000 3.207205534 0.10028439
    3920000 5760000 3.199388981 0.10030093
    2260000 2050000 3.209336519 0.100329794
    2740000 2800000 3.204200029 0.100354917
    2870000 3010000 3.213000059 0.100358635
    4020000 6190000 3.191919327 0.100362927
    3010000 3320000 3.198578358 0.100374177
    2430000 2320000 3.194086313 0.100381561
    2940000 3160000 3.206177235 0.100418426
    3240000 3830000 3.194527388 0.100547336

    Thanks,

    - Stephen

  • Sorry for the late reply Stephen,

    We tried out few resistor combination based on the values provided in the list and we saw improvements in the overall current consumption.

    Thanks,

    - Anand