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In cold climatic regions (25°C below zero) thermal comfort inside vehicle cabin plays a vital role for safety of driver and crew members. This comfortable and safe environment can be achieved either by utilizing available heat of engine coolant in conjunction with optimized in cab air circulation or by deploying more costly options such as auxiliary heaters, e.g., Fuel Fired, Positive Temperature Coefficient heaters. The typical vehicle cabin heating system effectiveness depends on optimized warm/hot air discharge through instrument panel and foot vents, air directivity to occupant's chest and foot zones and overall air flow distribution inside the vehicle cabin. On engine side it depends on engine coolant warm up and flow rate, coolant pipe routing, coolant leakage through engine thermostat and heater core construction and capacity.

The public transport in India is gradually shifting towards electric mobility. Long range in electric mobility can be served with High Voltage Battery (HVB), but HVB can sustain for its designed life if it’s maintained within a specific operating temperature range. Appropriate battery thermal management through Battery Cooling System (BCS) is critical for vehicle range and battery durability This work focus on two aspects, BCS sizing and its coolant flow optimization in Electric bus. BCS modelling was done in 1D CAE software. The objective is to develop a model of BCS in virtual environment to replicate the physical testing. Electric bus contain numerous battery packs and a complex piping in its cooling system. BCS sizing simulation was performed to keep the battery packs in operating temperature range.

In previous work, AC Compressor Cycling (ACC) was modeled by incorporating evaporator thermal inertia in Mobile Air Conditioning (MAC) performance simulation. Prediction accuracy of >95% in average cabin air temperature has been achieved at moderate ambient condition, however the number of ACC events in 1D CAE simulation were higher as compared to physical test [1]. This paper documents the systematic approach followed to address the challenges in simulation model in order to bridge the gap between physical and digital. In physical phenomenon, during cabin cooldown, after meeting the set/ target cooling of a cabin, the ACC takes place. During ACC, gradual heat transfer takes place between cold evaporator surface and air flowing over it because of evaporator thermal inertia.

In the past five years, Indian cities have been consistently appearing in the list of top 15 world’s most polluted cities. Every day, a common man in India spends more than 2 hours on the road due to numerous reasons, thus exposed to inhale highly polluted air. Further, the passenger car users is exposed to ~ 6 times more polluted air as compared to ambient air reason being the air is recirculated through the air conditioning system. Prolonged exposure to such polluted/ recirculated air shows increasing trend in respiratory illnesses, breathing discomfort and fatigue. This paper discusses the key challenges involved in incorporating cabin air filter as cabin air quality enhancer in current mobility solutions.

Mobile Air Conditioning (MAC) system provides year round thermal comfort to the occupants inside vehicle cabin. In present scenario, 1D CAE simulation tools are widely used for MAC system design, component sizing, component selection and cool down performance prediction. The MAC component sizing and selection mainly depends on cooling load which varies with ambient conditions, occupancy, cabin size, geometry and material properties. Therefore, detailed modeling of vehicle cabin is essential during MAC system digital validation as it helps to predict performance across wide number of contributing factors. There are two different methods available in 1D Simulation for vehicle cabin modeling, viz. ‘simple cabin’ and ‘advance cabin’. With the simple cabin modeling approach, vehicle cabin is modelled as a group of lumped masses, which only enables prediction of average vent and average cabin temperatures. In advance cabin modeling approach, vehicle cabin is modelled more comprehensively.

Vehicle thermal management system (VTMS) is a means of monitoring and controlling temperatures of vehicular components and aggregates to within optimum limits, thereby ensuring the proper functioning of the component or aggregate in an automobile. An integrated approach is required for developing VTMS, to satisfy the complex requirements of performance, reliability, fuel economy and human thermal comfort in modern vehicles. Fan motors and blowers play a crucial role in vehicle thermal management. These fan motors/ blower systems need to be designed in a manner such that there is minimum parasitic load on the prime mover. This work comprises performing Transient Powertrain Cooling (T-PTC) and Transient Air-conditioning (T-AC) simulation on a vehicle for prediction of parameters affecting fan operation of Condenser Radiator Fan Module (CRFM) during simulated city drive cycles.

The COVID-19 pandemic has driven the population to be extremely vigilant towards personal as well as shared hygiene necessitating use of facemask, maintaining social distancing, frequent hand wash and vehicle sanitization. Humans are exposed to pollutants such as Particulate Matter (PM), oxide of Sulphur (SOx), oxides of Nitrogen (NOx), Carbon Monoxide (CO), Ozone (O3), Total Volatile Organic Compound (TVOC) and pathogens such as fungi, bacteria, viruses (FBV) either through air or by direct contact with contaminated surfaces. In a vehicle cabin, occupants are exposed to both fresh and recirculating air through air-conditioning system and they also come in contact with touch points such as seats, steering wheel and armrest, which may be contaminated.

Electric vehicles (EVs) carries two main anxieties in users which are its range and battery life, hence these are important parameters to be taken care of during electric vehicle development. Range of EV depends on many parameters such as vehicle weight, heating ventilation and air conditioning (HVAC) system, battery cooling system (BCS), traction cooling system (TCS) and other electrical loads, which consumes power from a High Voltage (HV) battery. Severe hot ambient in India requires a big size HVAC system, on the other hand, the battery pack needs refrigerated cooling system to keep its temperature in control. Hence, the major parasitic consumers in an EV are HVAC and BCS. In order to enhance the overall efficiency, a trade-off between these two systems is crucial, as both the systems are served with common compressor and condenser in dual loop refrigerant circuit.

The objective of the work presented in this paper is to provide an overall CFD evaluation and optimization study of cabin climate control of air-conditioned (AC) city buses. Providing passengers with a comfortable experience is one of the focal point of any bus manufacturer. However, detailed evaluation through testing alone is difficult and not possible during vehicle development. With increasing travel needs and continuous focus on improving passenger experience, CFD supplemented by testing plays an important role in assessing the cabin comfort. The focus of the study is to evaluate the effect of size, shape and number of free-flow and overhead vents on flow distribution inside the cabin. Numerical simulations were carried out using a commercially available CFD code, Fluent®. Realizable k - ε RANS turbulence model was used to model turbulence. Airflow results from numerical simulation were compared with the testing results to evaluate the reliability.

This paper documents the approach followed to simulate the physical phenomenon of thermistor based AC compressor Cut-OFF/Cut-IN (AC compressor cycling) in 1-Dimensional Computer Aided Engineering (1D CAE) to enable Mobile Air Conditioning (MAC) performance prediction at different ambient conditions. Thermistor based AC compressor cycling logic is incorporated in MAC systems to prevent ice formation at evaporator core and liquid refrigerant flow to AC compressor. Currently, during MAC system performance simulation over a transient drive cycle, the 1D models are able to predict cabin cooldown performance for severe ambient conditions (>40°C, high solar load) with >95% accuracy, as in these cases AC compressor cycling due to thermistor doesn’t occur at higher ambient.

The air conditioning systems is the second energy consumer in the vehicle behind the powertrain with global energy consumptions of a few Kilowatts. In the case of Electric vehicles (EV), its consumption becomes critical to increase the range or potentially reduce battery size, weight and cost. In areas where high temperatures, solar radiation and high humidity are common, vehicle occupants rely constantly on the performance of the air conditioning for comfort and safety. Therefore, the AC (Air Conditioning) system is an ideal target to improve efficiency without an impact on occupier wellbeing. These are competitive advantages that would increase customer satisfaction and revenue potential. In fact, research shows that customers are ready to pay a higher price for sustainable products.

In developing nations, most passenger vehicles are equipped with mobile air conditioning (MAC) systems that work on Hydro Fluoro Carbons (HFC) based refrigerants. These refrigerants have a high global warming potential (GWP) and hence adversely affect the environment. According to the Kigali amendment to Montreal Protocol, Article-5 Group-2 countries including India must start phasing down HFCs from 2028 and replace them with low Global Warming Potential (GWP) refrigerants. One such class of low GWP refrigerant is Hydro Fluoro Olefins (HFO) In order to replace HFCs with HFOs in existing MAC systems, the various system performance parameters with the new refrigerant are required to be evaluated. Performance evaluation of MAC system is rendered quicker and cost-effective by deploying a digital simulation tool. There is good correlation and confidence established for MAC performance prediction with HFCs through 1D CAE.