diff --git a/freqtrade/templates/freqaiprimer.json b/freqtrade/templates/freqaiprimer.json
index 462a7667..8b2bb643 100644
--- a/freqtrade/templates/freqaiprimer.json
+++ b/freqtrade/templates/freqaiprimer.json
@@ -16,33 +16,33 @@
     },
     "buy": {
       "stake_divisor": 2,
-      "add_position_callback": 0.056,
-      "bb_length": 22,
+      "add_position_callback": 0.04,
+      "bb_length": 28,
       "bb_lower_deviation": 1.03,
-      "bb_std": 2.1,
+      "bb_std": 3.0,
       "bb_width_threshold": 0.01,
-      "h1_max_candles": 223,
-      "h1_max_consecutive_candles": 4,
-      "h1_rapid_rise_threshold": 0.061,
-      "max_entry_adjustments": 5,
+      "h1_max_candles": 218,
+      "h1_max_consecutive_candles": 3,
+      "h1_rapid_rise_threshold": 0.063,
+      "max_entry_adjustments": 2,
       "min_condition_count": 2,
-      "rsi_bull_threshold": 53,
-      "rsi_length": 10,
-      "rsi_oversold": 49,
-      "stochrsi_bull_threshold": 40,
-      "stochrsi_neutral_threshold": 20,
-      "volume_multiplier": 1.4
+      "rsi_bull_threshold": 48,
+      "rsi_length": 11,
+      "rsi_oversold": 44,
+      "stochrsi_bull_threshold": 32,
+      "stochrsi_neutral_threshold": 29,
+      "volume_multiplier": 1.6
     },
     "sell": {
       "exit_bb_upper_deviation": 0.98,
-      "exit_volume_multiplier": 1.9,
-      "roi_param_a": 0.06,
-      "roi_param_c": 0.0057,
-      "roi_param_k": 0.0088,
-      "rsi_overbought": 66
+      "exit_volume_multiplier": 2.0,
+      "roi_param_a": 0.062,
+      "roi_param_k": 0.0054,
+      "roi_param_t0": 0.0082,
+      "rsi_overbought": 53
     },
     "protection": {}
   },
   "ft_stratparam_v": 1,
-  "export_time": "2025-09-10 13:07:34.606541+00:00"
+  "export_time": "2025-09-10 20:55:14.197341+00:00"
 }
\ No newline at end of file
diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index 71818dd9..dc631cd2 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -109,7 +109,7 @@ class FreqaiPrimer(IStrategy):
     # 动态ROI参数 - 指数衰减函数参数 (ROI(t) = a·e^(-k·t) + c)
     roi_param_a = DecimalParameter(0.01, 0.1, decimals=3, default=0.05, optimize=True, load=True, space='sell')  # 初始ROI水平
     roi_param_k = DecimalParameter(0.001, 0.01, decimals=4, default=0.003, optimize=True, load=True, space='sell')  # 衰减速率
-    roi_param_c = DecimalParameter(0, 0.01, decimals=4, default=0.005, optimize=True, load=True, space='sell')  # 最低ROI水平
+    roi_param_t0 = DecimalParameter(0, 0.01, decimals=4, default=0.005, optimize=True, load=True, space='sell')  # 最低ROI水平
     # 出场条件阈值参数
     exit_bb_upper_deviation = DecimalParameter(0.98, 1.02, decimals=2, default=1.0, optimize=True, load=True, space='sell')
     exit_volume_multiplier = DecimalParameter(1.5, 3.0, decimals=1, default=2.0, optimize=True, load=True, space='sell')
@@ -548,78 +548,52 @@ class FreqaiPrimer(IStrategy):
             return -1.2 * atr / current_rate  # 基础1.2倍ATR止损
         return self.stoploss
     
-    def custom_exit(self, pair: str, trade: 'Trade', current_time, current_rate: float, 
+    def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
                     current_profit: float, **kwargs) -> float:
-        """
-        结合指数衰减ROI逻辑的动态止盈函数
-        - 根据交易持仓时间使用指数衰减公式计算动态止盈阈值
-        - 考虑当前市场状态调整止盈策略
-        - 仅支持多头交易
-        """
-        # 只支持多头
         if trade.is_short:
             return 0.0
-        
-        # 计算交易已持仓时间（分钟）
+
         trade_age_minutes = (current_time - trade.open_date_utc).total_seconds() / 60
-        
-        # 防止负数时间
         if trade_age_minutes < 0:
             trade_age_minutes = 0
-        
-        # 获取Hyperopt优化的指数衰减参数值
+
         a = self.roi_param_a.value
         k = self.roi_param_k.value
-        c = self.roi_param_c.value
-        
-        # 应用指数衰减公式计算动态ROI阈值
-        dynamic_roi_threshold = a * math.exp(-k * trade_age_minutes) + c
-        
-        # 确保ROI阈值为正数
-        dynamic_roi_threshold = max(dynamic_roi_threshold, 0.0)
-        
-        # 获取当前市场状态以调整止盈策略
-        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
-        current_state = dataframe['market_state'].iloc[-1] if 'market_state' in dataframe.columns else 'unknown'
-        
-        # 根据市场状态调整退出比例计算
-        exit_ratio = 0.0
-        
-        # 计算当前利润与动态ROI阈值的比值
-        if dynamic_roi_threshold > 0:
-            profit_ratio = current_profit / dynamic_roi_threshold
-        else:
-            profit_ratio = 0
-        
-        # 根据市场状态和利润比值确定退出比例
-        if profit_ratio >= 1.0:
-            # 利润达到或超过动态ROI阈值
-            if current_state == 'strong_bull':
-                # 强劲牛市中，允许部分利润奔跑
-                if profit_ratio < 1.5:
-                    exit_ratio = 0.5  # 达到ROI阈值时只退出50%
-                else:
-                    exit_ratio = 0.8  # 利润显著高于阈值时退出80%
-            elif current_state == 'weak_bull':
-                # 弱牛市中，平衡利润和风险
-                if profit_ratio < 1.2:
-                    exit_ratio = 0.6  # 达到ROI阈值时退出60%
-                else:
-                    exit_ratio = 0.9  # 利润高于阈值时退出90%
-            else:
-                # 其他市场状态下，更保守的策略
-                exit_ratio = 1.0  # 达到ROI阈值时全部退出
-        
-        # 记录动态止盈决策
-        #logger.info(f"[{pair}] 动态止盈: 持仓时间={trade_age_minutes:.1f}分钟, 当前利润={current_profit:.2%}, \
-                   # 动态ROI阈值={dynamic_roi_threshold:.4f}, 利润比值={profit_ratio:.2f}, \
-                   # 市场状态={current_state}, 退出比例={exit_ratio:.0%}")
-        
-        # 返回应退出的比例（0.0表示不退出，1.0表示全部退出）
-        return exit_ratio
-        
+        t0 = self.roi_param_t0.value
+
+        dynamic_roi_threshold = -a * math.atan(k * (trade_age_minutes - t0))
+        if dynamic_roi_threshold < 0:
+            dynamic_roi_threshold = 0.0
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        current_state = dataframe['market_state'].iloc[-1] if 'market_state' in dataframe.columns else (
+            'strong_bull' if dataframe['sma'].diff().iloc[-1] > 0.01 else 'weak_bull' if dataframe['sma'].diff().iloc[-1] > 0 else 'neutral'
+        )
+
+        entry_tag = trade.enter_tag if hasattr(trade, 'enter_tag') else None
+        profit_ratio = current_profit / dynamic_roi_threshold if dynamic_roi_threshold > 0 else 0
+
+        exit_ratio = 0.0
+        if profit_ratio >= 1.0:
+            if current_state == 'strong_bull':
+                exit_ratio = 0.5 if profit_ratio < 1.5 else 0.8
+            elif current_state == 'weak_bull':
+                exit_ratio = 0.6 if profit_ratio < 1.2 else 0.9
+            else:
+                exit_ratio = 1.0
+            if entry_tag == 'strong_trend':
+                exit_ratio *= 0.8
+
+        if dynamic_roi_threshold < 0:
+            exit_ratio = 1.0
+
+        logger.info(f"[{pair}] 动态止盈: 持仓时间={trade_age_minutes:.1f}分钟, 当前利润={current_profit:.2%}, "
+                    f"动态ROI阈值={dynamic_roi_threshold:.4f}, 利润比值={profit_ratio:.2f}, "
+                    f"市场状态={current_state}, entry_tag={entry_tag}, 退出比例={exit_ratio:.0%}")
+
+        return exit_ratio
+
 
-    
     def adjust_trade_position(self, trade: 'Trade', current_time, current_rate: float, 
                              current_profit: float, min_stake: float, max_stake: float, **kwargs) -> float:
         """
diff --git a/tools/hyperopt.sh b/tools/hyperopt.sh
index 6e252f80..07c32e61 100755
--- a/tools/hyperopt.sh
+++ b/tools/hyperopt.sh
@@ -243,8 +243,8 @@ docker-compose run --rm freqtrade hyperopt $PAIRS_FLAG \
   --enable-protections \
   --strategy-path /freqtrade/templates \
   --timerange ${START_DATE}-${END_DATE} \
-  -e 200 \
-  -j 3 \
+  -e 400 \
+  -j 4 \
   --hyperopt-loss SharpeHyperOptLossDaily \
   --spaces buy sell \
   --fee 0.0016