Python lib to talk to pylontech lithium batteries (US2000, US3000, ...) using RS485

Last update: Dec 28, 2022

Overview

python-pylontech

Python lib to talk to pylontech lithium batteries (US2000, US3000, ...) using RS485

What is this lib ?

This lib is meant to talk to Pylontech batteries using RS485. Sadly the protocol over RS485 is not some fancy thing like MODBUS but their own crappy protocol.

How to use this lib ?

First of all, you need a USB to RS485 converter. They are many available online for some bucks.

Then, you simply need to import the lib and start asking values:

>>> import pylontech
>>> p = pylontech.Pylontech()
>>> print(p.get_values())
Container: 
    CommandValue = 1
    NumberOfCells = 15
    CellVoltages = ListContainer: 
        3.325
        3.326
        3.325
        3.325
        3.325
        3.325
        3.325
        3.324
        3.324
        3.324
        3.326
        3.326
        3.326
        3.326
        3.326
    NumberOfTemperatures = 5
    AverageBMSTemperature = 30.01
    GroupedCellsTemperatures = ListContainer: 
        29.61
        29.61
        29.61
        29.61
    Current = 0
    Voltage = 49.878
    RemainingCapacity = 49.0
    TotalCapacity = 50.0
    CycleNumber = 0
>>> print(p.get_system_parameters())
Container: 
    CellHighVoltageLimit = 3.7
    CellLowVoltageLimit = 3.05
    CellUnderVoltageLimit = 2.9
    ChargeHighTemperatureLimit = 33.41
    ChargeLowTemperatureLimit = 26.21
    ChargeCurrentLimit = 10.2
    ModuleHighVoltageLimit = 54.0
    ModuleLowVoltageLimit = 46.0
    ModuleUnderVoltageLimit = 44.5
    DischargeHighTemperatureLimit = 33.41
    DischargeLowTemperatureLimit = 26.21
    DischargeCurrentLimit = -10.0

Dependencies

This lib depends on pyserial and the awesome construct lib.

Python lib to talk to pylontech lithium batteries (US2000, US3000, ...) using RS485

Related tags

Overview

python-pylontech

What is this lib ?

How to use this lib ?

Dependencies

Owner

Frank

商品推荐系统

Local-Global Stratified Transformer for Efficient Video Recognition

FMA: A Dataset For Music Analysis

Official implementation of our paper "LLA: Loss-aware Label Assignment for Dense Pedestrian Detection" in Pytorch.

Crowd-sourced Annotation of Human Motion.

The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"

Codes for building and training the neural network model described in Domain-informed neural networks for interaction localization within astroparticle experiments.

Official implementation for CVPR 2021 paper: Adaptive Class Suppression Loss for Long-Tail Object Detection

The aim of the game, as in the original one, is to find a specific image from a group of different images of a person's face

General neural ODE and DAE modules for power system dynamic modeling.

Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.

Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)

Code for our CVPR2021 paper coordinate attention

Learning 3D Part Assembly from a Single Image

Official pytorch implementation of DeformSyncNet: Deformation Transfer via Synchronized Shape Deformation Spaces

PyTorch implementation of MICCAI 2018 paper "Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector"

Stochastic Scene-Aware Motion Prediction

[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

Style transfer between images was performed using the VGG19 model

Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining