diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index adcda0a4..1076a1a0 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -385,12 +385,30 @@ class FreqaiDataKitchen:
         :param df: Dataframe containing all candles to run the entire backtest. Here
                    it is sliced down to just the present training period.
         """
+        # 创建数据副本并确保日期列时区一致性
+        df_copy = df.copy()
+        
+        # 标准化日期列的时区
+        if 'date' in df_copy.columns:
+            if hasattr(df_copy['date'], 'dt'):
+                if df_copy['date'].dt.tz is not None:
+                    df_copy['date'] = df_copy['date'].dt.tz_localize(None)
+        
+        # 确保timerange的日期也是无时区的
+        start_dt = timerange.startdt
+        stop_dt = timerange.stopdt
+        
+        if hasattr(start_dt, 'tz') and start_dt.tz is not None:
+            start_dt = start_dt.tz_localize(None)
+        if hasattr(stop_dt, 'tz') and stop_dt.tz is not None:
+            stop_dt = stop_dt.tz_localize(None)
+        
         if not self.live:
-            df = df.loc[(df["date"] >= timerange.startdt) & (df["date"] < timerange.stopdt), :]
+            df_copy = df_copy.loc[(df_copy["date"] >= start_dt) & (df_copy["date"] < stop_dt), :]
         else:
-            df = df.loc[df["date"] >= timerange.startdt, :]
+            df_copy = df_copy.loc[df_copy["date"] >= start_dt, :]
 
-        return df
+        return df_copy
 
     def find_features(self, dataframe: DataFrame) -> None:
         """
@@ -449,8 +467,15 @@ class FreqaiDataKitchen:
         cols = ["date"]
         cols.extend(user_cols)
 
-        dataframe_backtest.reset_index(drop=True, inplace=True)
-        merged_df = pd.concat([dataframe_backtest[cols], append_df], axis=1)
+        # 确保日期列的时区一致性，避免时区混用错误
+        dataframe_backtest_copy = dataframe_backtest[cols].copy()
+        if 'date' in dataframe_backtest_copy.columns:
+            if hasattr(dataframe_backtest_copy['date'], 'dt'):
+                if dataframe_backtest_copy['date'].dt.tz is not None:
+                    dataframe_backtest_copy['date'] = dataframe_backtest_copy['date'].dt.tz_localize(None)
+
+        dataframe_backtest_copy.reset_index(drop=True, inplace=True)
+        merged_df = pd.concat([dataframe_backtest_copy, append_df], axis=1)
         return merged_df
 
     def append_predictions(self, append_df: DataFrame) -> None: