diff --git a/Dynamic/Identification/ClosedLoopUnitIdentifier.cs b/Dynamic/Identification/ClosedLoopUnitIdentifier.cs
index e5765cb..5715c2d 100644
--- a/Dynamic/Identification/ClosedLoopUnitIdentifier.cs
+++ b/Dynamic/Identification/ClosedLoopUnitIdentifier.cs
@@ -94,6 +94,9 @@ public class ClosedLoopUnitIdentifier
                 }
             }
             // set "indicestoignore" to exclude values outside ymin/ymax_fit and umin_fit,u_max_fit
+             // 
+           // dataSet.DetermineIndicesToIgnore(fittingSpecs);
+
 
             // this variable holds the "newest" unit model run and is updated
             // over multiple runs, and as it improves, the 
@@ -296,6 +299,19 @@ public class ClosedLoopUnitIdentifier
                 identUnitModel.modelParameters.Fitting.WasAbleToIdentify = true;
                 identUnitModel.modelParameters.Fitting.StartTime = dataSet.Times.First();
                 identUnitModel.modelParameters.Fitting.EndTime = dataSet.Times.Last();
+                identUnitModel.modelParameters.Fitting.TimeBase_s = dataSet.GetTimeBase();
+
+                var uMaxList = new List<double>();
+                var uMinList = new List<double>();
+
+                for (int i = 0; i < dataSet.U.GetNColumns(); i++)
+                {
+                    uMaxList.Add(vec.Max(dataSet.U.GetColumn(i)));
+                    uMinList.Add(vec.Min(dataSet.U.GetColumn(i)));
+                }
+                identUnitModel.modelParameters.Fitting.Umax = uMaxList.ToArray();
+                identUnitModel.modelParameters.Fitting.Umin = uMinList.ToArray();
+
                 if (wasGainGlobalSearchDone)
                 {
                     identUnitModel.modelParameters.Fitting.SolverID = "ClosedLoop/w gain global search/2 step";
@@ -303,6 +319,9 @@ public class ClosedLoopUnitIdentifier
                 else
                     identUnitModel.modelParameters.Fitting.SolverID = "ClosedLoop local (NO global search)";
                 identUnitModel.modelParameters.Fitting.NFittingTotalDataPoints = dataSet.GetNumDataPoints();
+                identUnitModel.modelParameters.Fitting.NFittingBadDataPoints = dataSet.IndicesToIgnore.Count();
+
+
             }
             // closed-loop simulation, adds U_sim and Y_sim to "dataset"
             {
diff --git a/Dynamic/Identification/FittingInfo.cs b/Dynamic/Identification/FittingInfo.cs
index 77804e3..a6d06ae 100644
--- a/Dynamic/Identification/FittingInfo.cs
+++ b/Dynamic/Identification/FittingInfo.cs
@@ -32,6 +32,38 @@ public class FittingInfo
         /// </summary>
         public string SolverID { get; set; }
 
+
+        /// <summary>
+        /// A score that is 100% if model describes all variations 
+        /// and 0% if model is no better at describing variation than the flat average line.
+        /// Negative if the model is worse than a flat average line.
+        /// </summary>
+
+        public double FitScorePrc { get; set; }
+
+
+        /// <summary>
+        /// Number of bad data points ignored during fitting
+        /// </summary>
+        /// 
+        public double NFittingBadDataPoints { get; set; }
+
+        /// <summary>
+        /// Number of total data points (good and bad) available for fitting
+        /// </summary>
+        public double NFittingTotalDataPoints { get; set; }
+
+        /// <summary>
+        /// Start time of fitting data set
+        /// </summary>
+        public DateTime StartTime { get; set; }
+
+        /// <summary>
+        /// End time of fitting data set
+        /// </summary>
+        public DateTime EndTime { get; set; }
+
+
         /// <summary>
         /// The value of the R2 or root mean square of fitting,higher is better (used to choose among models)
         /// <para>
@@ -65,53 +97,22 @@ public class FittingInfo
 
         public double ObjFunValAbs { get; set; }
 
-
         /// <summary>
-        /// A score that is 100% if model describes all variations 
-        /// and 0% if model is no better at describing variation than the flat average line.
-        /// Negative if the model is worse than a flat average line.
-        /// </summary>
-
-        public double FitScorePrc { get; set; }
-
-        /// <summary>
-        /// Number of bad data points ignored during fitting
-        /// </summary>
-        /// 
-
-        public double NFittingBadDataPoints { get; set; }
-
-        /// <summary>
-        /// Number of total data points (good and bad) available for fitting
-        /// </summary>
-        public double NFittingTotalDataPoints { get; set; }
-
-        /// <summary>
-        /// Start time of fitting data set
+        /// The time base of the fitting dataset (model can still be run on other timebases)
         /// </summary>
-        public DateTime StartTime { get; set; }
 
-        /// <summary>
-        /// End time of fitting data set
-        /// </summary>
-        public DateTime EndTime { get; set; }
+        public double TimeBase_s;
 
-        /// <summary>
-        /// The maximum value of u seen in the data set
-        /// </summary>
-        public double[] Umax;
 
         /// <summary>
         /// The minimum value of u seen in the data set
         /// </summary>
         public double[] Umin;
 
-
         /// <summary>
-        /// The time base of the fitting dataset (model can still be run on other timebases)
+        /// The maximum value of u seen in the data set
         /// </summary>
-
-        public double TimeBase_s;
+        public double[] Umax;
 
 
         /// <summary>
diff --git a/TimeSeriesAnalysis.csproj b/TimeSeriesAnalysis.csproj
index 6d336de..fbb760c 100644
--- a/TimeSeriesAnalysis.csproj
+++ b/TimeSeriesAnalysis.csproj
@@ -14,7 +14,7 @@
 	<RunAnalyzersDuringLiveAnalysis>False</RunAnalyzersDuringLiveAnalysis>
     	<RepositoryUrl>https://github.com/equinor/TimeSeriesAnalysis.git</RepositoryUrl>
     	<PackageReadmeFile>readme.md</PackageReadmeFile>
-    	<Version>1.3.33</Version>
+    	<Version>1.3.34</Version>
     	<Company>Equinor</Company>
     	<Authors>Equinor</Authors>
     	<IncludeSymbols>true</IncludeSymbols>