diff --git a/tempControl.html b/tempControl.html
index 183af1b..cba45f2 100644
--- a/tempControl.html
+++ b/tempControl.html
@@ -1432,7 +1432,6 @@ <h3>📋 系统日志</h3>
                     episodeRewards: []
                 };
 
-                this.stepSinceLastDraw = 0;
             }
 
             setupCharts() {
@@ -1817,14 +1816,7 @@ <h3>📋 系统日志</h3>
                     this.trainCurveChart.data.datasets[1].data = tempTrace;
                     this.trainCurveChart.data.datasets[2].data = rewardTrace;
                     
-                    const CHART_UPDATE_INTERVAL = 1000;  // 每 20 步才 redraw
-
-                    this.stepSinceLastDraw++;
-                    if (this.stepSinceLastDraw >= CHART_UPDATE_INTERVAL || step === episodeEnd) {
-                        this.stepSinceLastDraw = 0;
-                        this.trainCurveChart.update('none');
-                        
-                    }
+                    this.trainCurveChart.update('none');
 
                 }
 
@@ -1879,12 +1871,8 @@ <h3>📋 系统日志</h3>
                     deltaT: parseFloat(document.getElementById('deltaT').value)
                 };
 
-                const rewardTrace = [];
-
-                this.stepSinceLastDraw = 0;
-
-                // 禁止训练期间使用固定 targetTemp
-                config.targetTemp = null;
+                // 禁止训练期间使用固定 targetTemp
+                config.targetTemp = null;
 
                 // 动态计算合理的目标温度范围，基于环境温度和最大功率
                 const minTemp = Math.max(25, config.roomTemp + 5); // 至少高于室温5度
@@ -1977,35 +1965,7 @@ <h3>📋 系统日志</h3>
                             ];
 
                             // 改进的奖励函数 - 接收水温和目标温度
-                            const reward = this.ddpgAgent.calculateReward(nextWaterTemp, episodeTarget, heatingPower, lastWaterTemp, step);
-                            rewardTrace.push(reward);
-                            this.log(`📈 [第${episode + 1}轮, 第${step + 1}步] 奖励: ${reward.toFixed(2)}`);
-
-                            if (this.trainCurveChart.data.datasets.length < 3) {
-                                this.trainCurveChart.data.datasets.push({
-                                    label: '每步奖励',
-                                    data: rewardTrace,
-                                    borderColor: '#E91E63',
-                                    backgroundColor: 'rgba(233, 30, 99, 0.1)',
-                                    fill: false,
-                                    tension: 0.1,
-                                    yAxisID: 'reward',
-                                    borderWidth: 1,
-                                    pointRadius: 0
-                                });
-                            } else {
-                                this.trainCurveChart.data.datasets[2].data = rewardTrace;
-                            }
-                            if (!this.trainCurveChart.options.scales.reward) {
-                                this.trainCurveChart.options.scales.reward = {
-                                    type: 'linear',
-                                    position: 'right',
-                                    title: { display: true, text: '奖励值' },
-                                    beginAtZero: false,
-                                    grid: { drawOnChartArea: false }
-                                };
-                            }
-                            this.trainCurveChart.update('none');
+                            const reward = this.ddpgAgent.calculateReward(nextWaterTemp, episodeTarget, heatingPower, lastWaterTemp, step);
 
                             // 改进的记忆函数，传入更多温度信息
                             this.ddpgAgent.remember(state, heatingPower, reward, nextState, false, waterTemp, episodeTarget, nextWaterTemp);
@@ -2093,14 +2053,14 @@ <h3>📋 系统日志</h3>
                             this.lossChart.update('none');
                         }
 
-                        if (this.tdLossChart) {
-                            this.tdLossChart.data.labels.push(episode + 1);
-                            this.tdLossChart.data.datasets[0].data.push(Math.abs(this.ddpgAgent.actorLoss || 0));
-                            this.tdLossChart.data.datasets[1].data.push(this.ddpgAgent.criticLoss || 0);
-                            this.tdLossChart.update('none');
-                        }
-
-                        // 检查训练稳定性并可能重置探索
+                        if (this.tdLossChart) {
+                            this.tdLossChart.data.labels.push(episode + 1);
+                            this.tdLossChart.data.datasets[0].data.push(Math.abs(this.ddpgAgent.actorLoss || 0));
+                            this.tdLossChart.data.datasets[1].data.push(this.ddpgAgent.criticLoss || 0);
+                            this.tdLossChart.update('none');
+                        }
+
+                        // 检查训练稳定性并可能重置探索
                         const resetExploration = this.ddpgAgent.checkTrainingStability(totalReward);
                         if (resetExploration) {
                             this.log(`🔄 第${episode + 1}轮: 重置探索策略，增大噪声至 ${(this.ddpgAgent.noiseScale * 100).toFixed(1)}%`, 'warning');
@@ -2128,19 +2088,17 @@ <h3>📋 系统日志</h3>
                             `平均: ${avgReward.toFixed(1)}`
                         );
 
-                        if (episode % 5 === 0 || episode === nEpisodes - 1) {
-                            // 计算温度误差指标
-                            const avgError = tempErrors.reduce((a, b) => a + b, 0) / tempErrors.length;
-                            const maxError = Math.max(...tempErrors);
-
-                            this.log(
-                                `📈 第${episode + 1}轮: 奖励=${totalReward.toFixed(1)}, ` +
-                                `目标温度=${episodeTarget.toFixed(1)}°C, ` +
-                                `噪声=${(this.ddpgAgent.noiseScale * 100).toFixed(1)}%, ` +
-                                `平均误差=${avgError.toFixed(2)}°C, ` +
-                                `到达目标用时=${stepsToTarget !== null ? stepsToTarget : '未达'}步`
-                            );
-                        }
+                        // 计算温度误差指标
+                        const avgError = tempErrors.reduce((a, b) => a + b, 0) / tempErrors.length;
+                        const maxError = Math.max(...tempErrors);
+
+                        this.log(
+                            `📈 第${episode + 1}轮: 奖励=${totalReward.toFixed(1)}, ` +
+                            `目标温度=${episodeTarget.toFixed(1)}°C, ` +
+                            `噪声=${(this.ddpgAgent.noiseScale * 100).toFixed(1)}%, ` +
+                            `平均误差=${avgError.toFixed(2)}°C, ` +
+                            `到达目标用时=${stepsToTarget !== null ? stepsToTarget : '未达'}步`
+                        );
 
                         // 每 5 轮或最后一轮，快速评估一次升温曲线
                         if (episode % 5 === 0 || episode === nEpisodes - 1) {