Painting is the largest energy consumption unit in ship repair enterprises, with annual electrical energy costs amounting to millions of dollars. The energy-saving model of painting business based on artificial intelligence, Internet of Vehicles (IoV) and big data technologies has become a current research hot spot. This paper takes a cargo ship of Youlian Shipyard as an example to improve the quality of special coating construction, reduce cost and increase efficiency. In the process of special coating construction, a comprehensive analysis of equipment usage in different compartments is carried out, and a compartment energy consumption analysis model based on combined weighting and Gray Fuzzy Comprehensive Evaluation is proposed. The model uses factors such as energy consumption, hours, and number of devices as evaluation indicators. Based on the fuzzy comprehensive evaluation, the gray correlation coefficients and comprehensive weights were weighted to obtain the final comprehensive evaluation results of each planning scheme, and then compare them to determine the optimal scheme. The results show that the grey fuzzy comprehensive evaluation model with combined weighting has better results than other models, and the evaluation results are scientific and reasonable. It has certain application value in multi-objective scheme optimization.

涂装是修船企业能耗最大的单位，每年的电能成本高达数百万美元。基于人工智能、车联网（IoV）和大数据技术的涂装业务节能模式已成为当前的研究热点。本文以友联船厂一艘货船为例，为提高特种涂料施工质量，降低成本，提高效率。在特种涂料施工过程中，对不同车厢的设备使用情况进行了综合分析，提出了基于组合加权和灰色模糊综合评价的车厢能耗分析模型。该模型以能耗、小时数、设备数量等因素作为评价指标。在模糊综合评价的基础上，对灰色相关系数和综合权重进行加权，得到各规划方案的最终综合评价结果，再进行比较，确定最优方案。结果表明，组合加权的灰色模糊综合评价模型效果优于其他模型，评价结果科学合理。在多目标方案优化中具有一定的应用价值。结果表明，组合加权的灰色模糊综合评价模型效果优于其他模型，评价结果科学合理。在多目标方案优化中具有一定的应用价值。结果表明，组合加权的灰色模糊综合评价模型效果优于其他模型，评价结果科学合理。在多目标方案优化中具有一定的应用价值。