diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index 35dbd6f0..3c33af14 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -51,6 +51,7 @@ class FreqaiPrimer(IStrategy):
     }
 
     def feature_engineering_expand_all(self, dataframe: DataFrame, period: int, metadata: dict, **kwargs) -> DataFrame:
+        # 保留原有指标
         dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
         dataframe["%-sma-period"] = ta.SMA(dataframe, timeperiod=period)
         dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
@@ -61,8 +62,24 @@ class FreqaiPrimer(IStrategy):
         dataframe["bb_upperband-period"] = upperband
         dataframe["bb_middleband-period"] = middleband
         dataframe["%-bb_width-period"] = (dataframe["bb_upperband-period"] - dataframe["bb_lowerband-period"]) / dataframe["bb_middleband-period"]
-
         dataframe["%-roc-period"] = ta.ROC(dataframe, timeperiod=period)
+
+        # 添加策略 B 的指标
+        dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period)  # 资金流指标
+        dataframe["%-adx-period"] = ta.ADX(dataframe, timeperiod=period)  # 趋势强度
+        dataframe["%-tema-period"] = ta.TEMA(dataframe, timeperiod=period)  # TEMA 指标
+        dataframe["%-relative_volume-period"] = dataframe["volume"] / dataframe["volume"].rolling(period).mean()  # 相对成交量
+        dataframe["%-close-bb_lower-period"] = dataframe["close"] / dataframe["bb_lowerband-period"]  # 收盘价/布林带下轨
+
+        # 数据清理
+        columns_to_clean = [
+            "%-rsi-period", "%-mfi-period", "%-sma-period", "%-ema-period", "%-adx-period",
+            "bb_lowerband-period", "bb_middleband-period", "bb_upperband-period",
+            "%-bb_width-period", "%-roc-period", "%-relative_volume-period", "%-close-bb_lower-period", "%-tema-period"
+        ]
+        for col in columns_to_clean:
+            dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0).ffill().fillna(0)
+
         return dataframe
 
     def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs) -> DataFrame: