How to normalize data without knowing the min and max values?
The minimum and maximum values are just known limits that are parts of the formula that reshapes the distribution of the data, so if a value is bigger than the previously known value the resulting feature scaling (Normalization) will be still appropriate. 

An alternative is z-scores if you don't feel like using minimum and maximum values.

x'= (x-x̄) / σ
Where x is the original feature vector, x̄  is the average of the vector x  is the mean of that feature vector and σ is its standard deviation.