## 1 Introduction  
The most significant element of the sound quality of a commercial vehicle's cab is its modal vibration, which includes the frequency characteristics of the vibration and the distribution of its vibration energy, especially for new-energy commercial vehicles, where there is no engine to act as the primary sound source and the interior noise or sound quality is mostly derived from the structural vibration of the body. Conventional acoustic and vibration control primarily emphasizes passive control, including sound absorption/vibration isolation design, vibration damping/vibration isolation design, and the prudent use of impedance mufflers [1; 2; 3]. The passive control scheme primarily has a good suppression effect on medium- and high-frequency vibration and noise, but the control effect is less suitable for structural modal vibration dominated by low- and medium-frequency vibration. It is also difficult for the passive control to improve the vibrating acoustic radiation quality and acoustic comfort requirements of the commercial vehicle cab [4; 5; 6]. Consequently, the active acoustic vibration control method is used to add a new vibration signal or sound signal to the original structural system, which is the secondary force source or secondary sound source, and combined with the real-time response algorithm control so that the original vibration signal and the secondary vibration signal of the evaluation monitoring point cancel and interfere with each other to achieve the aim of suppressing structural vibration and improving the quality of vibration and acoustic radiation in the vehicle [7; 8]. Among the most important pieces of hardware for the active control of structural noise and vibration are sensors and actuators. The actuators provide sound or vibration signals as secondary excitation loading terminals, and the sensors receive them as signal monitoring terminals [9]. The quantity and position of the secondary force or sound source of the actuator can be changed by the adjustable control algorithm to achieve active control of vibration and noise for the acoustic radiation brought on by structural modal vibration [10]. A key element in determining the efficiency of the system's sound quality management is the proper matching of the number and position of actuators/sensors, particularly for complicated structures with significant spatial irregularities such as commercial vehicle cabins. The inherent performance of the system can become uncontrollable due to improper quantity allocation and site selection, which will have the opposite impact on acoustic and vibration suppression [11; 12]. The controlled structure and control system have an impact on the number of active control devices, and it is easier to optimize objects with a small acoustic area and a basic structure. However, the control effect has not worked out well yet for irregular acoustic domain situations with numerous noise sources and complex structures [13; 14]. Currently, research on actuator/sensor count configurations is still scarce. On the other hand, scholars have thoroughly studied the best sensor/actuator configuration, including the theoretical optimization of the objective function and criteria, sane selection, and the creation of multiobjective optimization algorithms [15; 16; 17]. Scholars have been very interested in enhancing the efficiency, real time, and adaptability of the control algorithm since it directly influences the effect of active control of sound quality. Adaptively tracking noise signals, the ANE algorithm enhances sound quality in accordance with various requirements [18; 19]. However, the FELMS algorithm's control system is easier than the determination of the gain coefficient, which is more involved and harder to implement in hardware [20; 21; 22]. Instead of utilizing adaptive algorithms to change filters, the ANN technique uses neural networks to do so. It can more effectively handle non-linear difficulties and is still in the research stage [23; 24].