How to scale a variable when not knowing the maximum
If your model works in production, you should not retransform your scaler, you should transform new example like 150 is still the maximum value. (It will give you higher than 1, so its a bit problematic but possible solution is below)
However you can still label those example as outlier. 

Possible solution for that case: If you have high number of outliers/leverages, you should consider tree ensembles and/or regularized models. 

If your predictor is not on production, just add those examples to your train set and fit again since your sample in the first training would be different than the reality.