diff --git a/model_examples/PointPillar/README.md b/model_examples/PointPillar/README.md
index 0fac1e6b8ee31c8ad8eb62ca0dd90edb12103026..a4fbdc59c013b913d29241101f280db0991bcb61 100644
--- a/model_examples/PointPillar/README.md
+++ b/model_examples/PointPillar/README.md
@@ -195,10 +195,18 @@ code_path=model_examples/PointPillar
    ```
 2. 运行训练脚本。
    该模型支持单机单机8卡训练
+   
+   运行脚本支持命令行参数：
+   - '--num-npu'：NPU卡数，默认为8；
+   - '--batch-size': 每卡batch-size大小，默认为4；
    ```
    cd tools/test
+   # 8卡精度脚本
    bash train_pointpillar_full_8p.sh
+   (option) bash train_pointpillar_full_8p.sh --num-npu 8 --batch-size 4
+   # 8卡性能脚本
    bash train_pointpillar_performance_8p.sh
+   (option) bash train_pointpillar_performance_8p.sh --num-npu 8 --batch-size 4
    ```
    训练完成后，权重文件保存在当前路径下，并输出模型训练精度和性能信息
 
@@ -214,8 +222,8 @@ code_path=model_examples/PointPillar
 训练性能结果展示表
 | Exp | global batch size | FPS |
 | - | - | - |
-| 8p-竞品A | 256 | 486 |
-| 8p-Atlas 800T A2| 256 | 576 |
+| 8p-竞品A | 32 | 60.75 |
+| 8p-Atlas 800T A2| 32 | 70.79 |
 
 ## FAQ
 ### ImportError:/usr/local/gcc-7.5.0/lib64/libgomp.so.1:cannot allocate memory in static TLS block,
@@ -263,3 +271,4 @@ pip install protobuf
 
 [2025-06-12] **NEW:** PointPillar模型更新fps计算方式，更新性能指标
 
+[2025-08-25] **NEW:** PointPillar模型更新fps，更新脚本传参
diff --git a/model_examples/PointPillar/test/train_pointpillar_full_8p.sh b/model_examples/PointPillar/test/train_pointpillar_full_8p.sh
index 62bb80d4022565287f26352abefb506d2e0ae3ba..8530e6391ac213a79462e5e2775c0a425cfb43d4 100644
--- a/model_examples/PointPillar/test/train_pointpillar_full_8p.sh
+++ b/model_examples/PointPillar/test/train_pointpillar_full_8p.sh
@@ -14,19 +14,48 @@ fi
 
 #集合通信参数,不需要修改
 
-export RANK_SIZE=8
 RANK_ID_START=0
 
 #基础参数，需要模型审视修改
 #网络名称，同目录名称
 Network="PointPillar"
 #训练batch_size
-batch_size=32
+batch_size=4
+#训练NPU卡数
+num_npu=8
 #训练模型配置文件
 cfg_file="cfgs/kitti_models/pointpillar.yaml"
 #计算mAP时整除的倍率（检测类别数3，每个类别对应的指标数4）
 num_metric=12
 
+while [[ $# -gt 0 ]]; do 
+  case $1 in
+    --NUM-NPU|--num-npu)
+      num_npu="$2"
+      shift 2
+      ;;
+    --BATCH-SIZE|--batch-size)
+      batch_size="$2"
+      shift 2
+      ;;
+    --help)
+      echo "用法: $0 [选项]"
+      echo "选项:"
+      echo " --NUM-NPU 设置 NUM-NPU (默认: 8)"
+      echo " --BATCH-SIZE 设置 BATCH_SIZE (默认: 24)"
+      echo " --help 显示帮助信息"
+      exit 0
+      ;;
+    *)
+      echo "未知选项: $1"
+      echo "使用 --help 查看帮助"
+      exit 1
+      ;;
+  esac
+done
+
+echo "num_npu: $num_npu"
+echo "batch_size: $batch_size"
 
 #设置环境变量，不需要修改
 ASCEND_DEVICE_ID=0
@@ -48,6 +77,22 @@ if [ x"${etp_flag}" != x"true" ];then
     source  ${test_path_dir}/env_npu.sh
 fi
 
+# 备份config文件
+cp ${cfg_file} ${cfg_file}.bak
+
+#修改batchsize
+sed -i "s/BATCH_SIZE_PER_GPU:[[:space:]]*[0-9]\{1,\}/BATCH_SIZE_PER_GPU: $batch_size/g" ${cfg_file}
+
+#复原callback
+restore_config() {
+    if [ -f ${cfg_file}.bak ]; then
+        mv -f ${cfg_file}.bak ${cfg_file}
+    fi
+}
+
+#异常复原
+trap restore_config EXIT SIGINT SIGTERM ERR
+
 #训练开始时间，不需要修改
 start_time=$(date +%s)
 
@@ -66,7 +111,7 @@ done
 echo $PORT
 
 nohup python -m torch.distributed.launch \
-          --nproc_per_node=${RANK_SIZE} \
+          --nproc_per_node=${num_npu} \
           --rdzv_endpoint=localhost:${PORT} \
           train.py \
           --launcher pytorch \
@@ -77,12 +122,14 @@ wait
 end_time=$(date +%s)
 e2e_time=$(( $end_time - $start_time ))
 
+#复原batchsize
+sed -i "s/BATCH_SIZE_PER_GPU: $batch_size/BATCH_SIZE_PER_GPU: 4/g" cfgs/kitti_models/pointpillar.yaml
 
 #结果打印，不需要修改
 echo "------------------ Final result ------------------"
 #输出性能FPS，需要模型审视修改
 avg_time=`grep -a 'Batch time: ' ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk -F 'Batch time: ' '{print $2}'|awk 'NR>10'|awk -F '(' '{print $1}'|awk '{a+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
-FPS=`awk 'BEGIN{printf "%.3f\n", '$batch_size'*'${RANK_SIZE}'/'$avg_time'}'`
+FPS=`awk 'BEGIN{printf "%.3f\n", '$batch_size'*'${num_npu}'/'$avg_time'}'`
 
 #打印，不需要修改
 echo "Final Performance images/sec : $FPS"
@@ -92,13 +139,13 @@ echo "E2E Training Duration sec : $e2e_time"
 #训练用例信息，不需要修改
 BatchSize=${batch_size}
 DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+CaseName=${Network}_bs${BatchSize}_${num_npu}'p'_'acc'
 
 #获取性能数据，不需要修改
 #吞吐量
 ActualFPS=${FPS}
 #单迭代训练时长
-TrainingTime=`awk 'BEGIN{printf "%.2f\n",'${BatchSize}'*'${RANK_SIZE}'*1000/'${FPS}'}'`
+TrainingTime=`awk 'BEGIN{printf "%.2f\n",'${BatchSize}'*'${num_npu}'*1000/'${FPS}'}'`
 
 #打印精度数据，并打印到${CaseName}.log中
 declare -A metrics
@@ -114,7 +161,7 @@ done
 
 #关键信息打印到${CaseName}.log中，不需要修改
 echo "Network = ${Network}" > $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "RankSize = ${RANK_SIZE}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "RankSize = ${num_npu}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "BatchSize = ${BatchSize}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "DeviceType = ${DeviceType}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "CaseName = ${CaseName}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
diff --git a/model_examples/PointPillar/test/train_pointpillar_performance_8p.sh b/model_examples/PointPillar/test/train_pointpillar_performance_8p.sh
index 12e727e30100ec284956088c40e9ffbde0308264..b6bec642b5c0d40586289f978773298a28e3afea 100644
--- a/model_examples/PointPillar/test/train_pointpillar_performance_8p.sh
+++ b/model_examples/PointPillar/test/train_pointpillar_performance_8p.sh
@@ -14,19 +14,48 @@ fi
 
 #集合通信参数,不需要修改
 
-export RANK_SIZE=8
 RANK_ID_START=0
 
 #基础参数，需要模型审视修改
 #网络名称，同目录名称
 Network="PointPillar"
 #训练batch_size
-batch_size=32
+batch_size=4
+#训练NPU卡数
+num_npu=8
 #训练模型配置文件
 cfg_file="cfgs/kitti_models/pointpillar.yaml"
 #计算mAP时整除的倍率（检测类别数3，每个类别对应的指标数4）
 num_metric=12
 
+while [[ $# -gt 0 ]]; do 
+  case $1 in
+    --NUM-NPU|--num-npu)
+      num_npu="$2"
+      shift 2
+      ;;
+    --BATCH-SIZE|--batch-size)
+      batch_size="$2"
+      shift 2
+      ;;
+    --help)
+      echo "用法: $0 [选项]"
+      echo "选项:"
+      echo " --NUM-NPU 设置 NUM-NPU (默认: 8)"
+      echo " --BATCH-SIZE 设置 BATCH_SIZE (默认: 24)"
+      echo " --help 显示帮助信息"
+      exit 0
+      ;;
+    *)
+      echo "未知选项: $1"
+      echo "使用 --help 查看帮助"
+      exit 1
+      ;;
+  esac
+done
+
+echo "num_npu: $num_npu"
+echo "batch_size: $batch_size"
 
 #设置环境变量，不需要修改
 ASCEND_DEVICE_ID=0
@@ -48,6 +77,22 @@ if [ x"${etp_flag}" != x"true" ];then
     source  ${test_path_dir}/env_npu.sh
 fi
 
+# 备份config文件
+cp ${cfg_file} ${cfg_file}.bak
+
+#修改batchsize
+sed -i "s/BATCH_SIZE_PER_GPU:[[:space:]]*[0-9]\{1,\}/BATCH_SIZE_PER_GPU: $batch_size/g" ${cfg_file}
+
+#复原callback
+restore_config() {
+    if [ -f ${cfg_file}.bak ]; then
+        mv -f ${cfg_file}.bak ${cfg_file}
+    fi
+}
+
+#异常复原
+trap restore_config EXIT SIGINT SIGTERM ERR
+
 #训练开始时间，不需要修改
 start_time=$(date +%s)
 
@@ -66,7 +111,7 @@ done
 echo $PORT
 
 nohup python -m torch.distributed.launch \
-          --nproc_per_node=${RANK_SIZE} \
+          --nproc_per_node=${num_npu} \
           --rdzv_endpoint=localhost:${PORT} \
           train.py \
           --launcher pytorch \
@@ -79,12 +124,11 @@ wait
 end_time=$(date +%s)
 e2e_time=$(( $end_time - $start_time ))
 
-
 #结果打印，不需要修改
 echo "------------------ Final result ------------------"
 #输出性能FPS，需要模型审视修改
 avg_time=`grep -a 'Batch time: ' ${test_path_dir}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log|awk -F 'Batch time: ' '{print $2}'|awk 'NR>10'|awk -F '(' '{print $1}'|tail -100|awk '{a+=$1} END {if (NR != 0) printf("%.3f",a/NR)}'`
-FPS=`awk 'BEGIN{printf "%.3f\n", '$batch_size'*'${RANK_SIZE}'/'$avg_time'}'`
+FPS=`awk 'BEGIN{printf "%.3f\n", '$batch_size'*'${num_npu}'/'$avg_time'}'`
 
 #打印，不需要修改
 echo "Final Performance images/sec : $FPS"
@@ -94,17 +138,17 @@ echo "E2E Training Duration sec : $e2e_time"
 #训练用例信息，不需要修改
 BatchSize=${batch_size}
 DeviceType=`uname -m`
-CaseName=${Network}_bs${BatchSize}_${RANK_SIZE}'p'_'acc'
+CaseName=${Network}_bs${BatchSize}_${num_npu}'p'_'acc'
 
 #获取性能数据，不需要修改
 #吞吐量
 ActualFPS=${FPS}
 #单迭代训练时长
-TrainingTime=`awk 'BEGIN{printf "%.2f\n",'${BatchSize}'*'${RANK_SIZE}'*1000/'${FPS}'}'`
+TrainingTime=`awk 'BEGIN{printf "%.2f\n",'${BatchSize}'*'${num_npu}'*1000/'${FPS}'}'`
 
 #关键信息打印到${CaseName}.log中，不需要修改
 echo "Network = ${Network}" > $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
-echo "RankSize = ${RANK_SIZE}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "RankSize = ${num_npu}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "BatchSize = ${BatchSize}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "DeviceType = ${DeviceType}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log
 echo "CaseName = ${CaseName}" >> $test_path_dir/output/$ASCEND_DEVICE_ID/${CaseName}.log