Siemens S7-200 PLC data length and value range - Database & Sql Blog Articles

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When working with Siemens S7-200 PLCs, different data lengths can be used depending on the application requirements. These data lengths determine the range of values that can be stored and processed. Each instruction in the S7-200 system also requires specific data types to ensure proper operation.

The S7-200 series supports several data types, including Boolean (BOOL), integer (INT), real (FLOAT), and string (STRING). Each type has a defined data length and value range. Below is a summary of these ranges:

Real numbers are represented using a 32-bit single-precision format as per the ANSI/IEEE 754-1985 standard. They are accessed as double words and have an accuracy of up to six decimal places. This means that when using floating-point constants, you should specify no more than six digits after the decimal point for accurate results.

It's important to note that real number operations can sometimes lead to inaccuracies, especially when dealing with very large or very small values. This is due to the limitations of floating-point arithmetic.

For string data, each character is stored in a byte, with the first byte indicating the length of the string. A string can be between 0 and 254 characters long, plus one additional byte for the length. Therefore, the maximum length of a string is 255 bytes. However, the maximum length of a string constant is limited to 126 bytes.

Boolean data consists of two possible values: 0 or 1. This type is commonly used for logic control in PLC applications.

The S7-200 CPU does not support automatic data type detection. This means that the same data can be interpreted differently based on the instruction being used. For example, the value in VW100 can be treated as a signed integer in an addition operation or as an unsigned binary number in an XOR operation.

To make data handling more flexible, the S7-200 provides various conversion commands. These allow users to easily convert data between different formats and representations, improving compatibility and usability in complex systems.