Bus Cabin Noise Predictions of Large HVAC System using Total Noise Method 2023-01-1126

HVAC system design plays an important role in the acoustic comfort of passenger vehicles and becomes prominent in electric vehicles. In the case of buses, cabin volume is larger than in cars, thus HVAC system required inside buses are bigger in size, and to meet comfort requirement numerous blowers are used for airflow delivery. Due to multiple blowers rotating inside the mixing unit and large delivery of air inside of the large HVAC system airborne noise is produced during its operations. One way to evaluate this airborne noise with CFD methods would be using the traditional sliding mesh approach around all the blowers to resolve the flow and turbulence, which is computationally very expensive. However, ability to predict noise inside the bus cabin with lesser turnaround time is important to accommodate quick design changes at early product development stage. Consequently, there is a need to develop a methodology that predicts the cabin noise of large HVAC systems with a short turnaround time and is lesser expensive. This paper proposes a multiscale approach where airborne noise generated by a single blower in motion is predicted using commercial Lattice Boltzmann CFD software with a proportionally reduced HVAC system in an anechoic digital wind tunnel. This CFD noise prediction is used to replace all the blowers inside the mixing unit with virtual digital speakers to predict the cabin noise. This multiscale approach is divided into three steps and is defined as the Total Noise Approach in the paper. With the multiscale approach, overall SPL predicted inside the bus cabin at driver and rear passengers’ ear level were compared with the physical test measurements and has shown a good correlation. With the approach, computational cost and turnaround time is significantly less as compared to the flow resolving approach around all the blowers to predict cabin noise for the large HVAC systems and is therefore useful in designing and planning countermeasures during product development.