diff --git a/freqtrade/templates/freqaiprimer.json b/freqtrade/templates/freqaiprimer.json
index bbba52f9..0c8c74a4 100644
--- a/freqtrade/templates/freqaiprimer.json
+++ b/freqtrade/templates/freqaiprimer.json
@@ -18,33 +18,33 @@
       "add_position_callback": 0.043,
       "add_position_growth": 4.5,
       "add_position_multiplier": 0.86,
+      "max_entry_adjustments": 4,
       "stake_divisor": 9.3,
-      "bb_length": 30,
-      "bb_lower_deviation": 1.05,
-      "bb_std": 2.7,
-      "bb_width_threshold": 0.016,
-      "h1_max_candles": 173,
-      "h1_max_consecutive_candles": 2,
-      "h1_rapid_rise_threshold": 0.061,
-      "max_entry_adjustments": 3,
-      "min_condition_count": 3,
-      "rsi_bull_threshold": 50,
-      "rsi_length": 17,
-      "rsi_oversold": 49,
-      "stochrsi_bull_threshold": 32,
-      "stochrsi_neutral_threshold": 24,
-      "volume_multiplier": 1.8
+      "bb_length": 19,
+      "bb_lower_deviation": 1.04,
+      "bb_std": 3.0,
+      "bb_width_threshold": 0.026,
+      "h1_max_candles": 290,
+      "h1_max_consecutive_candles": 3,
+      "h1_rapid_rise_threshold": 0.078,
+      "min_condition_count": 2,
+      "rsi_bull_threshold": 45,
+      "rsi_length": 16,
+      "rsi_oversold": 42,
+      "stochrsi_bull_threshold": 31,
+      "stochrsi_neutral_threshold": 22,
+      "volume_multiplier": 1.2
     },
     "sell": {
-      "exit_bb_upper_deviation": 1.01,
-      "exit_volume_multiplier": 2.0,
-      "roi_param_a": -5e-05,
-      "roi_param_k": 148,
-      "roi_param_t": 0.144,
-      "rsi_overbought": 64
+      "exit_bb_upper_deviation": 0.98,
+      "exit_volume_multiplier": 1.5,
+      "roi_param_a": -0.00012,
+      "roi_param_k": 78,
+      "roi_param_t": 0.12,
+      "rsi_overbought": 69
     },
     "protection": {}
   },
   "ft_stratparam_v": 1,
-  "export_time": "2025-09-26 04:37:10.245352+00:00"
+  "export_time": "2025-09-28 05:08:17.958148+00:00"
 }
\ No newline at end of file
diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index 8b633e88..a0a4a015 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -260,7 +260,7 @@ class FreqaiPrimer(IStrategy):
     max_entry_adjustments = IntParameter(2, 5, default=3, optimize=True, load=True, space='buy')  # 最大加仓次数
     add_position_callback = DecimalParameter(0.02, 0.06, decimals=3, default=0.045, optimize=True, load=True, space='buy')  # 加仓回调百分比
     add_position_growth = DecimalParameter(1.5, 3.0, decimals=2, default=4.5, optimize=False, load=True, space='buy')  # 加仓金额增长因子，保留2位小数用于hyperopt优化
-    add_position_multiplier = DecimalParameter(0.2, 10.5, decimals=2, default=1.22, optimize=False, load=True, space='buy')  # 加仓间隔系数，保留2位小数用于hyperopt优化
+    add_position_multiplier = DecimalParameter(0.2, 10.5, decimals=2, default=0.86, optimize=False, load=True, space='buy')  # 加仓间隔系数，保留2位小数用于hyperopt优化
     stake_divisor = DecimalParameter(2.0, 12.0, decimals=2, default=9.3, optimize=False, load=True, space='buy')  # 加仓金额分母（小数类型，保留2位小数）
     
     # 线性ROI参数 - 用于线性函数: y = (a * (x + k)) + t
@@ -835,6 +835,11 @@ class FreqaiPrimer(IStrategy):
         
         # 获取默认的基础仓位大小
         default_stake = self.stake_amount
+                
+        # 从kwargs获取最小和最大仓位限制
+        min_stake = kwargs.get('min_stake', 0.0)
+        max_stake = kwargs.get('max_stake', default_stake)
+
         
         # 根据波动系数调整仓位大小
         # 波动率与仓位大小成反比关系
@@ -847,7 +852,7 @@ class FreqaiPrimer(IStrategy):
             adjusted_stake = default_stake
         
         # 确保调整后的仓位在允许的范围内
-        adjusted_stake = max(self.min_stake_amount, min(adjusted_stake, self.stake_amount))
+        adjusted_stake = max(min_stake, min(adjusted_stake, max_stake))
         
         #logger.info(f"[{pair}] 基于波动系数调整仓位: 波动系数={volatility_coef:.2f}, 默认仓位={default_stake:.2f}, 调整后仓位={adjusted_stake:.2f}")