diff --git a/cal_and_val/thermal/cal_hev.py b/cal_and_val/thermal/cal_hev.py
index 7028a9f9..4a0acacd 100644
--- a/cal_and_val/thermal/cal_hev.py
+++ b/cal_and_val/thermal/cal_hev.py
@@ -224,7 +224,7 @@ def get_mod_soc(sd_dict):
     return np.array(sd_dict['veh']['pt_type']['HybridElectricVehicle']['res']['history']['soc'])
 
 def get_exp_soc(df):
-    return df['HVBatt_SOC_high_precision_PCAN__per']
+    return df['HVBatt_SOC_high_precision_PCAN__per'] / 100
 
 save_path = Path(__file__).parent / "pymoo_res" / Path(__file__).stem
 save_path.mkdir(exist_ok=True, parents=True)
diff --git a/cal_and_val/thermal/val_hev.py b/cal_and_val/thermal/val_hev.py
index 108afe8b..e8609002 100644
--- a/cal_and_val/thermal/val_hev.py
+++ b/cal_and_val/thermal/val_hev.py
@@ -1,12 +1,12 @@
 import pandas as pd
 
-from cal_hev import cal_mod_obj, val_mod_obj,save_path
+from cal_hev import cal_mod_obj, val_mod_obj, save_path
 
 res_df = pd.read_csv(save_path / "pymoo_res_df.csv")
 res_df['euclidean'] = (
     res_df.iloc[:, len(cal_mod_obj.param_fns):] ** 2).sum(1).pow(1/2)
 best_row = res_df["euclidean"].argmin()
 best_df = res_df.iloc[best_row, :]
-param_vals = res_df.iloc[best_row, : len(cal_mod_obj.params)].to_numpy()
+param_vals = res_df.iloc[best_row, : len(cal_mod_obj.param_fns)].to_numpy()
 
 
diff --git a/python/fastsim/pymoo_api.py b/python/fastsim/pymoo_api.py
index 40a28d33..06e3f4cb 100644
--- a/python/fastsim/pymoo_api.py
+++ b/python/fastsim/pymoo_api.py
@@ -132,7 +132,7 @@ def __post_init__(self):
 
     def update_params(self, xs: List[Any]):
         """
-        Updates model parameters based on `x`, which must match length of self.params
+        Updates model parameters based on `x`, which must match length of self.param_fns
         """
         assert len(xs) == len(self.param_fns), f"({len(xs)} != {len(self.param_fns)}"