Browse Topic: Air conditioning
The automotive air-conditioning service ports task force conducted a field survey with MACS (Mobile Air Climate Systems Association) in June 2021. The scope of this survey was to determine the types of failures reported primarily at member service shops related to automotive air-conditioning service ports.
The increasing electrification of vehicles means that heating, ventilation and air conditioning systems have a broader range of tasks and a different priority assessment. In electric cars, air conditioning systems are not only responsible for cooling the passenger compartment, but also for controlling the battery temperature, particularly during rapid charging, which represents a high-load operating point. Furthermore, achieving high thermodynamic efficiency is desirable, as this directly impacts the range of electric cars. The elimination of the combustion engine as a major source of noise prioritizes the noise, vibration and harshness behavior of the refrigerant compressor for product selection. To investigate the vibration and acoustic behavior, as well as the fluid dynamic forces resulting from the cyclic compression principle of an electric refrigerant compressor, a test rig was developed that allows compressors to be operated and measured in isolation in an anechoic chamber under various defined operating conditions. This test rig has been expanded in two ways within the scope of this work. Firstly, the compressor can be either rigidly attached to a dead mass using a VDA mount or measured while suspended freely. Secondly, a new R744-compatible refrigeration circuit has been added to the test rig, enabling compressors operating with the environmentally friendly refrigerant CO₂, which has so far only been used by a few manufacturers in selected models, to be tested. Measurement results obtained using this test rig provide valuable insight into the vibration behavior and sound spectra of the refrigerant compressor's fluid, structural, and airborne noise when operating at different points.
Electric Vehicles (EVs) are rapidly transforming the automotive landscape, offering a cleaner and more sustainable alternative to internal combustion engine vehicles. As EV adoption grows, optimizing energy consumption becomes critical to enhancing vehicle efficiency and extending driving range. One of the most significant auxiliary loads in EVs is the climate control system, commonly referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a substantial portion of the battery's energy—especially under extreme weather conditions—leading to a noticeable reduction in vehicle range. This energy demand poses a challenge for EV manufacturers and users alike, as range anxiety remains a key barrier to widespread EV acceptance. Consequently, developing intelligent climate control strategies is essential to minimize HVAC power consumption without compromising passenger comfort. These strategies may include predictive thermal management, cabin pre-conditioning, zonal climate control, and integration with renewable energy sources. By implementing such energy-efficient solutions, EVs can achieve better range performance, improved user satisfaction, and greater environmental benefits. Modern EV climate control systems increasingly rely on intelligent features such as Auto mode, which dynamically adjusts fan speed, airflow direction, and temperature settings based on real-time cabin and ambient conditions. By leveraging sensor data and adaptive control algorithms, Auto mode optimizes thermal comfort while minimizing unnecessary energy expenditure. This automated regulation plays a crucial role in reducing HVAC-related power consumption, thereby contributing to overall range improvement and enhancing system efficiency without compromising passenger comfort. This study focuses on the development of three distinct Auto mode calibration levels for each set condition, designed to achieve the same cabin temperature with varying dynamic responses and energy consumption profiles. In Auto mode, the cabin temperature is regulated through intelligent control of compressor speed, blower speed, and evaporator temperature. While all Auto levels can maintain the desired setpoint, the time required to reach this temperature and the system’s responsiveness to sudden thermal loads can vary significantly. This study introduces three distinct calibration profiles, each engineered to achieve the same cabin temperature under different dynamic conditions and energy consumption levels. These profiles allow users to choose between faster thermal response or reduced power usage, effectively enabling a trade-off between immediate comfort and extended driving range
The automotive industry has undergone significant transformation with the adoption of electric vehicles (EVs). However, the inadequate driving range is still a major limitation and to tackle range anxiety, the focus has shifted to energy management strategies for optimal range under different driving conditions. Developing an optimal energy management algorithm is crucial for overcoming range anxiety and gaining a competitive edge in the market. This paper introduces Dynamic Energy Management Strategy (DEMS) for electric vehicles (EVs), designed to optimize battery usage and extend the driving range. Utilizing vehicle digital twin model, DEMS estimates energy consumption across Eco, Normal, and Sports driving modes by analyzing vehicle velocity profiles and pedal inputs. By calculating actual battery consumption and identifying excess power usage, DEMS operates in a closed loop to periodically assess the power gap based on real-time vehicle conditions, including HV components like the Electric Drive system, DCDC, E-compressor and E-Heater; and intelligently allocates energy to each component, ensuring optimal performance. DEMS automatically selects the best drive mode and strategically manages energy distribution, prioritizing essential functions such as the drivetrain, followed by comfort features like heating or air conditioning, and luxury features like ambient lighting or seat massagers. This dynamic energy allocation is continuously adjusted to maximize efficiency, making EVs more efficient and extending their range. Simulations demonstrate that this approach can extend battery life and driving range, offering a promising solution for commercial EVs with existing battery technology. This strategy advances the sustainability and functionality of battery electric vehicles in modern transportation ecosystems.
The HVAC (Heating, Ventilation, and Air conditioning) system is designed to fulfil the thermal comfort requirement inside a vehicle cabin. Human thermal comfort primarily depends upon an occupant’s physiological and environmental condition. Vehicle AC performance is evaluated by mapping air velocity and local air temperature at various places inside the cabin. There is a need to have simulation methodology for cabin heating applications for cold climate to assess ventilation system effectiveness considering thermal comfort. Thermal comfort modelling involves human manikin modeling, cabin thermal model considering material details and environmental conditions using transient CAE simulation. Present study employed with LBM (Lattice-Boltzmann Method) based PowerFLOW solver coupled with finite element based PowerTHERM solver to simulate the cabin heat up. Human thermal comfort needs physiological modelling; thus, the in-built Berkeley human comfort library is used in simulation. Human thermal modelling includes metabolic rate of heat production with effects of clothing in external ambient conditions. Once human thermal modelling in a controlled environment stabilized, LBM-based solver used to predict the convective heat transfer phenomenon. Thereafter, conduction and radiation effects were solved using a coupling approach in PowerTHERM. Physical tests conducted in a controlled environment of climate chambers. Simulation results obtained correlated with experimental data. Occupants’ thermal comfort evaluated using the Berkeley comfort model. The current process further highlights the impact of heater capacity variation on in-cabin air temperature and passenger comfort level. The proposed method is helpful in thermal comfort prediction for passenger vehicles at cold ambient comfort requirements, heater capacity, and airflow delivery system effectiveness. Current process is found more effective where heater capacity and thermal comfort balance prediction are sensitive to two heaters, discussed in this paper.
The interior noise and thermal performance of the passenger compartment are critical criteria for ensuring driving comfort [1]. This paper presents the optimization of air conditioning (AC) compressor noise, specifically for the low-powered 1.0 L - ICE engine paired with a 120 cc IVDC compressor. This combination is quite challenging due to the high operational load & higher operating pressure. To enhance better in-cabin cooling efficiency, compressor’s operating efficiency must be improved, which necessitates a higher displacement of the compressor. However, increased displacement results in greater internal forces which leads to more structure-borne induced noise inside the cabin. For this specific configuration, the compressor operating pressure reached up to 25 bars under most driving conditions. During dynamic driving scenario, a metallic tonal noise from the compressor was reported in a compact vehicle segment. It is reported as very annoying to passengers inside. A comprehensive root cause analysis was conducted, including Transfer Path Analysis (TPA), evaluation of compressor fixation points stiffness, and dynamic noise signature analysis. The investigation revealed that the metallic noise was a combination of moaning and whining sounds, primarily caused by internal excitation forces within the compressor. These forces generated dominant excitations at high operating pressures, resulting in the observed tonal noise. Several countermeasures were explored, including changes to the compressor pulley ratio to decouple engine firing frequency excitations, modifications to the AC pipe bends to reduce excitation forces, and optimization of acoustic mass and compressor mounting stiffness. Collaboration work has been done with the supplier focused on fine-tuning the Mass Flow Control Valve (MFCV) settings [6] and adjusting compressor shaft tolerance. The most effective solutions were the compressor pulley ratio change and the modification of the compressor’s planetary plate angle, which together achieved an improvement of approximately 6 dB(A) in compressor order noise, significantly reducing customer-perceived annoyance. As a result, key NVH (Noise, Vibration, and Harshness) design rules have been established and implemented
In both internal combustion engine (ICE) and electric vehicles, Heating, Ventilation, and Air Conditioning (HVAC) systems have become significant contributors to in-cabin noise. Although significant efforts have been made across the industry to reduce noise from airflow handling systems, especially blower noise. Nowadays, original equipment manufacture’s (OEMs) are increasingly focusing on mitigating noise generated by refrigeration handling systems. Since the integration of refrigeration components is vital for the overall Noise Vibrations and Harshness (NVH) refinement of a vehicle, analysing the impact of each HVAC component during vehicle-level integration is essential. This study focused on optimizing the NVH performance of key refrigeration components, including the AC compressor, thermal expansion valve (TXV), suction pipe, and discharge line. The research began with a theoretical investigation of the primary noise and vibration sources, particularly the compressor and TXV, followed by an analysis of vibration transmission paths through the refrigerant lines. To ensure an optimal acoustic and thermal balance among these four components, both design parameters and dynamic operating characteristics were studied for their impact on thermoacoustic performance inside the vehicle. The compressor was identified as a major source of low and mid frequency noise and vibration, while pressure pulsations in the refrigerant lines contributed to structure-borne and airborne noise. These issues were addressed by developing new design guidelines aimed at improving isolation and damping characteristics. Specific efforts included designing stair-gated modal decoupling strategies to avoid resonance between the compressor bracket and engine or aggregate excitation frequencies. In addition, the standing wave behaviour in the suction and discharge lines was analysed to identify and control resonant modes that amplified NVH issues. The TXV was also studied in detail, with a particular focus on mid-frequency noise caused by its internal dynamics. Parameters such as spring stiffness, natural frequency, and superheat setting behaviour were optimized to improve cabin acoustic comfort. The outcome of this paper is a comprehensive component-level NVH validation combined with practical design guidelines for minimizing integration-related noise and vibration issues in HVAC systems. These findings provide a robust framework for engineers to enhance both thermal performance and in-cabin acoustic refinement, ensuring superior comfort in modern vehicles.
Thermal Management System (TMS) for Battery Electric Vehicles (BEV) incorporates maintaining optimum temperature for cabin, battery and e-powertrain subsystems under different charging and discharging conditions at various ambient temperatures. Current methods of thermal management are inefficient, complex and lead to wastage of energy and battery capacity loss due to inability of energy transfer between subsystems. In this paper, the energy consumption of an electric vehicle's thermal management system is reduced by a novel approach for integration of various subsystems. Integrated Thermal Management System (ITMS) integrates air conditioning system, battery thermal management and e-powertrain system. Characteristics of existing integration strategies are studied, compared, and classified based on their energy efficiency for different operating conditions. A new integrated system is proposed with a heat pump system for cabin and waste heat recovery from e-powertrain. Various cooling and heating strategies for battery are identified for different ambient temperatures. An ITMS valve functioning is explained for each scenario depending on vehicle operating condition and ambient temperature.
In automotive systems, efficient thermal management is essential for refining vehicle performance, enhancing passenger comfort, and reducing MAC Power Consumption. The performance of an air conditioning system is linked to the performance of its condenser, which in turn depends on critical parameters such as the opening area, radiator fan ability and shroud design sealing. The opening area decides the airflow rate through the condenser, directly affecting the heat exchange efficiency. A larger opening area typically allows for greater airflow, enhancing the condenser's ability to dissipate heat. The shroud, which guides the airflow through the condenser, plays a vital role in minimizing warm air recirculation. An optimally designed shroud can significantly improve the condenser's thermal performance by directing the airflow more effectively. Higher fan capacity can increase the airflow through the condenser, improving heat transfer rates. However, it is essential to balance fan capacity with energy consumption to achieve optimal performance. This study investigates the impact of varying these parameters on vehicle-level A/C performance and MAC Power Consumption. By systematically altering the condenser opening area, changing the shroud configuration, and adjusting the radiator fan capacity, we aim to find best conditions that enhance A/C performance and effect MAC Power Consumption. Experimental data were collected through a series of controlled tests, the results were analysed to decide the correlation between these variables A/C performance metrics such as average grill temperatures, refrigerant pressure and MAC Power Consumption. The findings provide valuable insights for automotive engineers and designers, highlighting the importance of these factors in achieving efficient as well as effective A/C systems in passenger vehicles.
Compressor durability is a critical factor for ensuring the long-term reliability of Mobile Air Conditioning (MAC) systems in passenger vehicles. This study presents a software based strategy for enhancing compressor life using Smart Fully Automatic Temperature Control (FATC), requiring no additional hardware. The proposed approach leverages existing inputs from the FATC and Engine Management System (EMS) to intelligently manage compressor operation, with a focus on addressing challenges related to prolonged non-usage. In extended inactivity scenarios such as during cold weather, vehicle exportation, storage, or breakdowns, lubrication oil tends to settle in the compressor sump, leaving internal parts dry. Sudden reactivation at high engine speeds under such conditions can cause increased friction, wear and even compressor seizure. To mitigate this, an intelligent reactivation protocol has been developed and integrated into the Climate Control Module (CCM). This protocol continuously monitors parameters such as ambient and evaporator temperatures, solar load and engine RPM to detect extended inactivity. Upon detection, it initiates a controlled compressor activation sequence involving short duration clutch engagement cycles, allowing gradual lubrication and preventing mechanical stress. The strategy includes a multivariable detection framework and dynamic threshold adaptation that tailors activation logic to real-time environmental and operational conditions. A Smart transition mechanism ensures smooth switching between safe and regular operation modes. Preliminary testing shows that this method effectively minimizes dry starts, reduces mechanical wear and supports long term compressor health. The proposed strategy offers a cost effective and robust solution for improving compressor durability, lowering maintenance costs and enhancing user satisfaction.
Noise generated by a vehicle’s HVAC (Heating, Ventilation, and Air Conditioning) system can significantly affect passenger comfort and the overall driving experience. One of the main causes of this noise is resonance, which happens when the operating speed of rotating parts, such as fans or compressors, matches the natural frequency of the ducts or housing. This leads to unwanted noise inside the cabin. A Campbell diagram provides a systematic approach to identifying and analyzing resonance issues. By plotting natural frequencies of system components against their operating speeds, Test engineers can determine the specific points where resonance occurs. Once these points are known, design changes can be made to avoid them—for example, adjusting the blower speed, modifying duct stiffness, or adding damping materials such as foam. In our study, resonance was observed in the HVAC duct at a specific blower speed on the Campbell diagram. To address this, we opted to optimize the duct design instead of changing the blower speed. This approach helped eliminate resonance at that operating point, reducing noise in the cabin. By applying the Campbell diagram tool, HVAC noise can be minimized, resulting in a quieter cabin and an improved driving experience.
In order to improve the efficiency of verification and optimization of control strategies for air-conditioning systems, a thermal management platform is established based on a rapid control prototyping (RCP) approach in the article. The platform is composed of a HVAC hardware bench, a real-time control system, and a control software model. This article describes the overall architecture of the platform, the control strategy, and an efficient method for development and optimization of air-conditioning control strategies. The cooling and heating modes of the air conditioner are tested. The results show that the control strategy can be directly modified via the platform to improve the performance of the whole system. The experimental results show that after modifying the control strategy, the cooling effect of the air conditioner is optimized and the cooling time is reduced by 10.6%. The CLTC cycle is also tested in this work to verify the dynamic control performance of the air-conditioning system. This approach provides a solution for optimizing the control strategy of air-conditioning systems in the future and make a significant contribution to the development of thermal management system testing.
Electrification of vehicles plays an important role in the transformation process towards sustainable mobility in the individual and transport sector. As a result, new challenges must be met during the development process regarding the vehicles overall energy management system. A key challenge is the development of thermal management systems to optimize overall vehicle efficiency and to minimize ageing effects of the powertrain components while maintaining passenger comfort. Efficiency and ageing effects are highly dependent on the conditioning state of the powertrain components due to their high thermal sensitivity with simultaneously narrow thermal operating limits. Comfort functions like cabin air conditioning must be fulfilled as well, which must be considered by the thermal management system. To develop innovative solutions for thermal management systems at an early stage of the development process, thermal emulation can be used to substitute hardware components. Therefore, thermal representative simulation models calculate the waste heat of the components, which is then transferred to the testbed by thermo-hydraulic emulators. This enables testing of components and systems in early stages of development under real boundary conditions. Furthermore, operation strategies for the thermal management systems, considering interactions between thermally relevant subsystems, can be developed at an early stage. This study shows the development of a compact and scalable thermal emulator as well as the requirements for an optimal development environment at a thermal testbed.
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