随着大模型与汽车工业的快速发展及智能化演进，智能汽车的音效算法在提升用户座舱声学体验方面发挥着重要作用。本文基于大模型技术的发展，对智能汽车音效算法及功能、系统架构及应用进行了全面综述。首先，介绍车载音效领域的发展历程与技术现状，展望在大模型技术驱动下该领域的应用场景和趋势。接着，从车载音效听感、噪声管理、智能化体验三个维度，分析 10 余个产品功能及算法优势，并探讨各个算法在车内广泛应用面临的一系列问题及解决方案；最后，基于大模型能力对市面上在售车辆的音频系统进行数据学习和模型训练，围绕音频芯片选型、功率放大器、扬声器等维度，为其他车辆音效系统提升提供参考方案。本综述旨在基于大模型技术为智能汽车音效领域的研究提供参考，进而推动该技术在汽车领域的广泛应用。

With the rapid development and intelligent evolution of large language models(LLMs) and the automotive industry, sound effect algorithms for vehicle play a crucial role in enhancing the acoustic experience within the cabin.In this paper,a comprehensive review of sound effect algorithms, functions, system architectures, and applications for vehicle based on the LLMs was provided. Firstly, it introduces the development history and current technological status of the in-vehicle sound effects,along with future application scenarios and trends in this field driven by LLMs. Next, it analyzes the advantages of more than 10 product functions and algorithms from three dimensions: sound reproduction, noise management, and intelligent experience.The paper further discusses challenges and near-term solutions for implementing these algorithms in vehicles.Finally, Large language models conduct data-driven learning and model training on audio systems of commercially available vehicles.This process enabled the development of a reference framework for enhancing in-vehicle acoustic systems across three critical dimensions: audio chip, amplifiers, and speaker. This review aims to serve as a reference for research on LLMs based smart car sound effects, promoting widespread adoption in the automotive field.