Prediction and Optimization of Noise radiation from a Heavy-Duty Commercial Vehicle Transmission using Statistical Energy Analysis

Heavy Duty (HD) linehaul vehicles are majorly used in transportation of goods and heavy loads between different cities or long distances. Considering the current trend, payload capacity of these heavy-duty trucks are increasing due to constant increase in the load demand. Due to which engine torques of these HD vehicles are increasing which in turn increases the transmission input torque. At higher torque levels, gear excitation also increases and transmission becomes more susceptible towards higher noise radiation. Global vehicle pass-by noise regulations for HD commercial vehicles are becoming more stringent. Historically transmissions have been considered a secondary noise source but with overall HD vehicle noise becoming quieter, the transmission can be more of a significant noise contributor. Hence, noise radiation from the transmission is also an important factor to be considered in the design phase. Gear whine is the major concern for sound radiation from the transmission. The gear whine simulation and acoustic radiation analysis of the transmission is a crucial but very time-consuming part of the product development cycle. To achieve the requirement of lighter weight components, product designers can select lighter materials and thinner walls for the transmission enclosure. With decreased enclosure thickness and the use of lighter materials, the acoustic analysis performed by traditional methods (FEM and BEM) is difficult to handle computationally because of the higher modal density of the system. This paper provides an approach for calculating sound radiation in SPL (sound pressure level) from the enclosure. The analysis is performed on ribbed and unribbed enclosure structures. This work includes the sensitivity analysis of all the parameters influencing the SPL. The results from the SEA method are compared with the actual test data for final validation. The obtained results are in good agreement with test data with an overall accuracy of +/- 3 dBA.