对6061铝合金板（铝板）和DP590钢板进行冷金属过渡（CMT）搭接焊，应用正交法对焊接工艺参数进行优化；运用BP神经网络对铝钢板的焊接变形量进行预测，将预测结果以反变形方式作用于铝钢板并测定其焊后变形量。结果表明：最佳工艺参数范围为送丝速度3.6~3.9 m·min^-1、焊接速度0.66~0.70 m·min^-1、弧长修正0~5%、铝板厚度1.5~2.0 mm；采用优化工艺参数焊接后接头能承受的最大试验力达到3 400 N，焊缝金属化合物层的厚度最大约7.43 mm；BP神经网络对焊接变形量的预测结果与试验结果吻合，反变形处理后铝钢板的焊接变形得到明显改善，变形量由0.67 mm降至约0.12 mm，该预测方法有效。

Cold metal transfer (CMT) lap welding was performed on 6061 aluminum alloy sheet (aluminum sheet) and DP590 steel sheet. The welding process parameters were optimized by orthogonal method. BP neural network was used to predict welding deformation amount of the aluminum/steel sheets. The predicted results were applied to the aluminum/steel sheets, and then the welding deformation amounts were measured. The results show that the optimal process parameters were listed as follows:wire feed speed of 3.6-3.9 m·min^-1, welding speed of 0.66-0.70 m·min^-1, arc length correction of 0-5% and aluminum sheet thickness of 1.5-2.0 mm. The maximum test force that the joint welded with the optimal process parameters can withstand was up to 3 400 N, and the maximum thickness of the metal compound transition layer in weld was about 7.43 mm. The prediction results for welding deformation amount by the BP neural network were in good agreement with the experimental results. After anti-deformation, the welding deformation of the aluminum/steel sheets decreased significantly, with deformation amount decreasing from 0.67 mm to 0.12 mm, indicating that the prediction method was valid.