Cabin Heating Research Articles

Numerical analysis of the energy efficiency measures for improving the truck cabin thermal performance

This paper presents the numerical analysis of the thermal performance of a truck cabin. The results obtained for a standard truck cabin setup are compared to the configurations with energy saving measures implemented. As a very promising energy efficiency measure, the application of the infrared panels is considered. Based on the radiative heat transfer mechanism, the infrared panels influence directly all inner cabin surfaces. This includes also the truck cabin occupants, whose perception of the indoor comfort reaches neutral values much faster and at lower ambient air temperatures. As a result, there is much lower energy demand for the cabin heating, required for maintaining the desired indoor comfort. The preliminary numerical analysis indicates the energy saving potential of around 30% for this innovative cabin thermal concept, as compared to the original energy demand for the traditional cabin heating configuration.

Experimental evaluations of Berkeley thermal sensation and comfort models in electric vehicle cabin under cold outdoor conditions

As the automobile industry is transitioning toward electric vehicles, manufacturers have started implementing local warmers alongside cabin heating, ventilation, and air conditioning (HVAC) systems for effective thermal comfort management. However, optimal operating strategies need to be developed for integrating local warmers with HVAC systems. Although the Berkeley models comprising local/overall thermal sensation and comfort models offer insights in this regard, they lack follow-up assessments for occupants transitioning from very cold states. In this study, Berkeley models were evaluated using two sets of experimental data collected in a transient vehicle cabin under cold outdoor conditions: test (A) with cabin HVAC alone and test (B) with both HVAC and local warmers. The findings confirm the satisfactory performances of the Berkeley models for predicting overall sensation and comfort, with a maximum root mean-squared error (RMSE) of 0.15. The local comfort model performed poorly with the original coefficients across both datasets (maximum RMSE of 1.96). Therefore, the model coefficients were regressed for the dataset from test A and validated against the dataset from test B to achieve a maximum RMSE of 0.49. With these regressed coefficients, it was observed that moving toward a neutral whole-body state diminished the potential to maximize local comfort. Conversely, the local sensation model showed poor agreement (maximum RMSE of 1.9); we confirmed that accurate adaptive setpoint temperatures are a prerequisite for ensuring good predictions from the model. These findings are expected to contribute toward future efforts in using Berkeley models to formulate effective local warmer–HVAC operational strategies in electric vehicles.

Design optimization of finned multi-tube PCM heat exchanger for enhancing EV energy performance

This study presents an optimized design of a finned multi-tube phase change material-based thermal energy storage system for electric vehicle thermal management, addressing the challenge of low battery efficiency in cold climates. While finned multi-tube designs are recognized for their thermal advantages, their application in electric vehicles has been underexplored. Previous research often overlooks the full operational cycle of electric vehicles, including charging (melting), discharging (solidification), and driving conditions. This work bridges the gap by optimizing the thermal energy storage design using a multi-objective genetic algorithm to enhance both thermal efficiency and energy density. The optimized design reduces melting and solidification times by 68.6% and 60.3%, respectively, and increases energy density by 4.9% compared to the initial design. The study further integrates the optimized thermal energy storage system into an electric vehicle thermal management strategy, analyzing its performance under real-life driving cycles in various ambient temperatures. This integration reduces total energy consumption by 20.6% compared to a baseline system. These findings offer a novel approach to improving the driving range of electric vehicles in cold climates by minimizing power demand on electric batteries for cabin heating.

Investigation of cabin heating in electric vehicles with integrating solar cells and heat storage systems

In recent years, the production and usage of electric vehicles have been encouraged due to zero emissions, efficiency, and economic factors. Efficient cabin heating and thermal management in electric vehicles are crucial for enhancing passenger comfort, extending battery life, and optimizing overall energy usage, thus contributing to the sustainability and practicality of electric transportation. Heating the cabin of electric vehicles in winter has a negative effect on range. Therefore, methods are being researched to use energy efficiently without sacrificing passenger comfort and minimizing the effect on the vehicle's range. This study presents an innovative radiator design specifically crafted for Electric Vehicles (EVs), leveraging solar panels to heat water for the radiator. This system enables the vehicle to harness solar energy for heating a water tank while stationary, effectively serving as an energy storage reservoir. Upon vehicle movement, the radiator system activates to disperse the stored thermal energy throughout the cabin, ensuring superior thermal comfort. Consequently, optimizing battery range is achieved as the heating load typically leads to significant range reductions. From the obtained results in experiment 2, the results indicated that the cabin temperature rose from 3 °C to around 15 °C within a few minutes, reflecting an increase of approximately 12 °C. According to the results, this indicates that there will be a reduction in energy consumption of between 1.9 % and 3 % for a one-hour travel range in this electric vehicle. The findings of this investigation demonstrate that utilizing warm water energy storage effectively enhances cabin thermal management.

Utilizing multilayer perceptron for machine learning diagnosis in phase change material‐based thermal management systems

AbstractElectric vehicles encounter significant challenges in colder climates due to reduced battery efficiency at low temperatures and increased electricity demand for cabin heating, which impacts vehicle propulsion. This study aims to address these challenges by implementing a thermal management system utilizing Phase Change Materials (PCMs) and validating the performance of a Multilayer Perceptron (MLP) model in predicting PCMs behavior and battery temperature distributions. The study employs an MLP model trained with 160 samples of diverse heat inputs, including pulsating, constant, wiener, discharging, and random temperatures. The model uses these temperatures as inputs and liquid fractions as target values. Performance evaluation is conducted using the MATLAB platform and is benchmarked against existing approaches, such as Long Short‐term Memory (LSTM), spatiotemporal convolutional neural network (CNN), and pooled CNN‐LSTM. The MLP model's accuracy in predicting PCMs phase transitions is validated by comparing predicted liquid fractions with numerically obtained values. Additionally, this study forecasts temperature distributions within a standard battery pack under various discharge scenarios, considering the performance of commercial lithium‐ion batteries. The proposed MLP model demonstrates high efficacy, achieving a correlation of up to 0.999 and root mean squared error below 0.013 compared with numerical results.

Electric-thermal collaborative control and multimode energy flow analysis of fuel cell hybrid electric vehicles in low-temperature regions

The energy flow distribution characteristics of electric vehicles operating in various propulsion modes and all climatic scenarios have not been thoroughly explored. To achieve effective electric-thermal collaborative energy management, intelligent control methods must be applied considering various climatic conditions to alleviate mileage anxiety. In this study, we developed a novel electric–thermal collaborative energy management strategy based on an improved deep neural network and energy quantification model to increase the global energy conversion efficiency. The complete energy consumption distribution characteristics are summarized under various strategies and propulsion modes based on an experiment data collected by the vehicle control unit that involves battery self-heating, cabin heating, acceleration consumption, and fuel consumption in the temperature range of −10°C-35 °C. Our findings indicate that, for a fuel cell hybrid bus in the cycle including the initial cabin heating process, the heating consumption in the pure electric mode was 9.9 kWh/cycle and 13 kWh/cycle when the ambient temperature is −2 °C and −10 °C, respectively, accounting for 33 % and 42 % of the total consumption, respectively. After using the waste heat from the fuel cell, the consumption of electric heating under the same conditions is only 3.7 kWh/cycle. In the high-temperature scenario, the cabin cooling consumption is 3.26 kWh/cycle, accounting for only 18 % of the total energy consumption. Finally, in low-temperature scenarios, the electric–thermal collaborative strategy reduced the cost by 14.7 % and 9.2 % in the pure electric and hybrid modes, respectively. Thus, our approach significantly improves energy utilization and conversion efficiency, especially at low temperatures.

Investigating the effect of lower body local radiant warming on occupant thermal comfort in battery electric vehicles during cold conditions

The wintertime decrease in the driving range of battery electric vehicles (BEVs), partially attributed to cabin heating with improper setpoints, necessitates the improvement of occupant thermal comfort with reduced energy consumption. While local warming shows promise, understanding its impact on occupant comfort with thermal transients from cabin heating, ventilation, and air conditioning (HVAC) is limited. To address this gap, we investigated thermal perception in twenty-five participants under three distinct warming modes within BEVs operating through typical winter conditions: HVAC alone, HVAC with continuous lower body local radiant warming (LRW), and HVAC with periodic lower body LRW. Results show that the rapid change in skin temperature from lower body local warming does not immediately improve comfort. While a significant improvement in comfort (p < 0.05) is observed with lower body warming, it becomes evident only when the cabin transients subside. Consequently, we propose a framework that advocates for reducing HVAC setpoint and control of LRW of the lower body based on occupant preferences. Our feasibility study demonstrates a 45.3 % reduction in energy consumption by reducing the HVAC setpoint from 25 to 18 °C. These findings enhance the prospects for efficient thermal comfort management in BEVs.

Performance comparison of a direct heat pump using R1234yf and indirect heat pumps using R1234yf and R290 designed for cabin heating of electric vehicles

When using R290 as an alternative to R1234yf for heat pump (HP) cabin heating systems, indirect system (IDS) should be employed to address safety issues owing to its high flammability. However, studies comparing the performance of a direct system (DS) using R1234yf and an IDS using R290 are limited. In this study, the performance characteristics of DS-HPR1234yf, IDS-HPR1234yf, and IDS-HPR290 were compared to verify the feasibility of applying R290 to cabin heating systems in electric vehicles. Compared with DS-HPR1234yf, the heating capacity (QHP) and compressor work (WHP) of IDS-HPR1234yf decreased by 2.8% and increased by 4.5% on average, respectively, owing to the system configuration effects. QHP and WHP of IDS-HPR290 increased by 42.1% and 51.0%, respectively, over those of DS-HPR1234yf owing to the refrigerant and system configuration effects. Thus, at −20 °C, COPHP (HP's coefficient of performance) of IDS-HPR290 was 1.8, which was 4.9% higher than that of DS-HPR1234yf, owing to the high decrease rate of WHP. Additionally, considering the use of HP and positive temperature coefficient (PTC) heaters, COPHP + PTC of IDS-HPR290 was 6.7–22.1% higher than that of DS-HPR1234yf owing to its superior QHP, and the driving range (DR) of IDS-HPR290 was 7.2–20% higher than that of DRPTC.

The Macromolecular Design of Poly(styrene-isoprene-styrene) (SIS) Copolymers Defines their Performance in Flexible Electrothermal Composite Heaters.

Electric cars are desirable for their environmental and economic benefits yet face limitations in range in cold weather due to the increased energy demands for cabin heating. To provide efficient heating for vehicles, flexible composite electrothermal heaters offer a viable solution owing to their lightweight design, efficiency, and adaptability for use within and beyond vehicle interiors. The current study aims to improve electrothermal heater stability and performance by understanding the impact of the polymer structure on composite properties. We explore how the presence and molecular structure of olefinic bonds within the polyisoprene block of styrenic triblock copolymers affect thermal stability and performance. Composite electrothermal heaters were fabricated by dispersing carbon black (CB) as the heating material in three triblock copolymer matrices, poly(styrene-1,4-isoprene-styrene) (1,4-SIS), poly(styrene-3,4-isoprene-styrene) (3,4-SIS), and its hydrogenated version poly(styrene-ethylene-propylene-styrene) (SEPS). The chemical structure and thermal properties of each copolymer were linked to electrothermal performance measurements of composite heaters to establish structure-function relationships. Notably, 3,4-SIS with 28 wt % CB demonstrated the highest thermal and electrical conductivity, resulting in uniform heat distribution. The outcomes unambiguously demonstrate that the olefinic structure of SIS copolymers enhances the electric and thermal conductivity, leading to enhanced electrothermal performance of prototype heaters compared to that of the hydrogenated copolymer.

Development of PCM-based shell-and-tube thermal energy storages for efficient EV thermal management

Electric vehicles face significant challenges in cold climates. Battery efficiency decreases, and cabin heating demands additional electricity, which diminishes the energy available for vehicle propulsion. In this context, a thermal energy storage system based on a phase change material (PCM) with diverse designs of shell-and-tube heat exchangers is investigated to meet cabin thermal load demands independently. A simulation model for a two-phase PCM heat exchanger is developed and validated using experimental data. The comparison revealed average temperature differences of 1.59 K and 1.61 K for the melting and solidification processes, respectively. Compared to the single tube design, the heat transfer performance of finned multitube design improved the melting process and reduced the melting time by 92.9% and reduced the solidification time by 87.6%. The average heat transfer rate of the finned multitube during the solidification process is 2.9 times higher than that of the single tube. Additionally, the use of PCM incorporating different types of nanomaterials is explored to enhance the melting and solidification performance through increased thermal conductivity. The graphene nanoplatelet PCM exhibited the most substantial improvements in thermal conductivity, resulting in melting and solidification time reductions by 54.2% and 48.9%, respectively.

Adaptive Integrated Thermal Management System for a Stable Driving Environment in Battery Electric Vehicles

With an increase in global warming, battery electric vehicles (BEVs), which are environmentally friendly, have been rapidly commercialized to replace conventional vehicles with internal combustion engines. Unlike traditional internal combustion engine vehicles, the powertrain system of BEVs operates with high efficiency, resulting in lower heat generation. This poses a challenge for cabin heating under low-temperature conditions. Conversely, under high-temperature conditions, the operating temperature of a high-voltage battery (HVB) is lower than the ambient air temperature, which makes cooling through ambient air challenging. To overcome these challenges, in this study, we proposed an integrated thermal management system (ITMS) based on a heat pump system capable of stable thermal management under diverse climatic conditions. Furthermore, to assess the ability of the proposed ITMS to perform thermal management under various climatic conditions, we integrated a detailed powertrain system model incorporating BEV specifications and the proposed ITMS model based on the heat pump system. The ITMS model was evaluated under high-load-driving conditions, specifically the HWFET scenario, demonstrating its capability to perform stable thermal management not only under high-temperature conditions, such as at 36 °C, but also under low-temperature conditions, such as at −10 °C, through the designated thermal management modes.

Super-capacitor integration into hybrid vehicle power source

The plug-in hybrid vehicle based on the concept of battery operated vehicle with strong electrical motor(s) and electrochemical battery is for thermal comfort of crew and for occasional elongated travel range completed by generator, which is designed on average traction power only and during of journey is mainly used in co-generative run for cabin heating. Such vehicle efficiency can be improved by the third power source, specifically used only for acceleration and regenerative braking purposes. That role is optimal for super-capacitor, which has very good charging efficiency and can store the energy from braking to the next acceleration. Both these actions are usually very fast with high power in very short time. Its sizing and voltage control is investigated in this paper.

Methods for increasing the efficiency of climate control systems for electric buses

Increasing the range of an electric bus on a single battery charge is an important task facing electric bus developers. The auxiliary system that consumes the largest amount of electricity is the air conditioning system. This paper examines the main methods for increasing the efficiency of a climate control system and evaluates them using numerical methods using a verified one-dimensional mathematical model. The following methods were chosen to improve efficiency: the most suitable refrigerants, the use of an internal heat exchanger of a vapor compression unit, the recovery of heat from the air removed from the interior electric bus in the evaporator of a vapor compression unit, and the use of heat from electrical equipment in the climate control system. The greatest efficiency in cooling and heating modes is shown by the use of refrigerants R404a, R410a and R507a in the vapor compression unit. The use of an internal heat exchanger in a vapor compression unit allows an increase in coefficient of performance by 11%. The combined use of cabin heat in the evaporator of the vapor compression unit and the internal heat exchanger allows the coefficient of performance to be increased by 27%. Using the heat of electrical equipment allows you to increase the coefficient of performance in heat pump mode by 20%. The most promising is the combined use of the above methods to reduce the cost of air conditioning in the cold season.

A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning

A Novel Energy Management Strategy for PHEV Considering Cabin Heat Demand Under Low Temperature Based on Reinforcement Learning

A three-heat source segmented heating control strategy based on waste heat recovery technology for electric vehicles

The control strategy of thermal management systems is crucial for electric vehicles to ensure thermal comfort of the cabin and thermal safety of the battery and motor. However, this will also impact the energy consumption of the vehicle. In this study, a three-heat source segmented heating control strategy was proposed to reduce the heating energy consumption of electric vehicles, with the three sources denoted motor waste heat, air, and positive temperature coefficient (PTC) heaters. Specifically, a simulation model of an integrated thermal management system for heat pump air conditioning, motor thermal management, and battery thermal management systems was first established and validated using published experimental results. Subsequently, the performance of three cabin heating modes was investigated based on the standard driving cycle. The optimal opening and closing strategies for each mode were discussed to ensure the temperature requirements of the cabin, and the optimal method for using motor waste heat and the PTC heater to heat the battery at low temperatures was explored. The segmented heating control strategy was developed by determining the heating priority for the battery and cabin, as well as the heating capacity of heating modes using air source. Compared to the traditional heating strategy of the cabin and battery, the proposed control strategy could reduce energy consumption by 18.49 % while running at an ambient temperature of − 10 °C for 2.5 h.

Study on integrated thermal management system of hydrogen fuel cell vehicles based on heat pump air conditioning

An integrated thermal management system (VITMS) of hydrogen fuel cell vehicle (FCV) is proposed to solve the issues of poor temperature control and high energy consumption in current dispersed TMS. The vehicle energy integration is realized by coupling the key subsystems of cabin, fuel cell, power battery and motor through the waste-heat source heat pump (WSHP). The temperature control capability under extreme working conditions are analyzed. The energy consumption of three heating modes under extreme cold conditions is evaluated. The results show that VITMS has excellent thermal control performance and can realize fourteen work modes such as cooling, heating, preheating, defrosting and energy recovery, ensuring the optimal temperature ranges and temperature uniformity of fuel cell, power battery, motor, and cabin. VITMS using WSHP offers superior energy saving effect in extreme cold conditions, which can reduce equivalent hydrogen consumption by 12.21% and 3.6%, and increase maximum driving range by 29.34% and 8% compared to PTC and air-source heat pump (ASHP). The cabin heating time using WSHP can be reduced by 34.5% compared to ASHP, ensuring all-weather ride comfort and extending the vehicle's driving range in low temperatures. Annual CO2 emission is 52.13% and 36.17% lower than diesel and electric buses.

Performance of an automotive reversible CO2 heat pump system during periodic frosting-defrosting cycles

Electric vehicles (EVs) have seen rapid growth in the global market share due to the demand for low-emission commuting. However, EVs face the challenge of range anxiety in cold weather due to the capacity degradation of lithium-ion batteries and the increased demands of cabin and battery heating. Heat pump (HP) technology improves the heating efficiency compared to resistive heating, but in cold and humid weather, frost can grow on the outdoor evaporator and reduce the efficiency of the HP system. In this paper, experiments are carried out to assess the impacts of ambient temperature and relative humidity (RH) on the capacity and efficiency of a transcritical CO2 HP system during the continuous frosting-defrosting cycles under some challenging operating conditions (ambient temperature below 0 °C and RH over 80%). Moreover, the mass of frost accumulated during the frosting period, and that of water retained, drained, and vaporized during the defrosting period are measured and analyzed. The results show that when the ambient temperature decreases from 0 to −10 °C, the peak value of the heating capacity in the first frosting or HP mode period reduces from 4.85 to 3.54 kW, and the coefficient of performance (COPhp) drops from 1.61 to 1.47, but the operating time of the first frosting period significantly increases from 32 to 108 min. Similarly, lowering RH from 90% to 80% at 0 °C also helps to extend the operating time of the frosting period in one frosting-defrosting cycle from 32 to 84 min. In addition, with the current commonly used defrost initiation criterion, which is the air-side pressure drop across the outdoor evaporator increasing by five times, the heating capacity and system efficiency drop by less than 10% at the end of one frosting period. This indicates the potential for a longer operating time of the HP system which could reduce the undesirable impact on the passengers’ comfort during the reversed cycle defrosting.

Exergy analysis of heat pump air conditioning systems for pure electric vehicle use with low-GWP refrigerants

The exergy analysis of low-global warming potential (GWP) alternative refrigerants, R1234yf, R152a and R744 for heat pump air conditioning (HPAC) systems used in pure electric vehicles (EVs) is conducted via simulation. The results reveal that the system exergy efficiencies (SEEs) of R1234yf-HPAC and R152a-HPAC under identical cooling or heating capacity are similar due to their close thermodynamic properties. The largest exergy destruction component in R1234yf- and R152a-HPACs is the compressor. While for R744-HPAC, the compressor and expansion valve cause major exergy destruction. Moreover, the results also indicate that the SEE of R744-HPAC is at least 20 % lower than that of R1234yf-HPAC when producing identical cooling capacity, while it is on average twice that of R1234-HPAC when producing identical heating capacity. Furthermore, the measures to improve SEE of HPAC systems with different refrigerants are discussed by examining the effects of varying operating conditions. It is suggested to lower compressor speed under both cooling and heating conditions, increase condenser airflow or reduce evaporator airflow of R1234yf-, R152a- and R744-HPACs under cooling condition; for cabin heating, it is advisable to increase the evaporator airflow or decrease condenser airflow for R1234yf- and R152a- HPACs and enlarge condenser airflow for R744-HPAC to elevate SEE.

A novel design of heating system using phase change material for passenger car cabin in cold starting conditions

In this paper, the use of exhaust waste heat energy stored in a latent heat thermal energy storage (LHTES) system for cabin heating of a passenger car at cold climate conditions was investigated by experimental and computational fluid dynamics (CFD). A liquid circulation system was installed for this purpose, consisting of two heat exchangers, one in the passenger car's rear compartment and the other in which the phase change material (PCM) in the LHTES system was stored. Commercial RT55 paraffin wax was used as PCM, and tap water was used as heat transfer fluid (HTF). Experimental and CFD analysis studies, which started at 283 K cabin interior temperature, were continued for 1500 sec (25 min). Before the experiments, the cabin interior of the passenger car was cooled up to 283 K with the air conditioning system, and the air conditioning system was kept on at a setting where the cabin interior temperature would remain constant at 283 K during the experiments. Thus, real cold climate conditions were provided for the experimental study. As a result, it has been observed that with the new cabin heating system, thermal comfort conditions for people are provided after the first five minutes, and this temperature can be maintained throughout the experiment. So much so that the cabin temperature increased from 283 K to 295 K in five minutes and reached approximately 297 K at the end of the experiment with a slow rate of increase. Furthermore, the difference in RT55 temperatures between the experimental and CFD analysis results is less than 3% during the cabin interior heating period.

NMPC-Based Integrated Thermal Management of Battery and Cabin for Electric Vehicles in Cold Weather Conditions

One of the major obstacles along the way of electric vehicles' (EVs') wider global adoption is their limited driving range. Extreme cold or hot environments can further impact the EV's range as a significant amount of energy is needed for cabin and battery temperature regulation while the battery's power and energy capacity are also impeded. To overcome this issue, we present an optimal control strategy based on nonlinear model predictive control (NMPC) for integrated thermal management (ITM) of the battery and cabin of EVs, where the proposed NMPC simultaneously optimizes the EV range and cabin comfort in real time. Firstly, the components of the designed ITM system are introduced and control-oriented modeling is done. Secondly, to demonstrate and validate the benefits of the proposed ITM, an optimal control problem is defined and dynamic programming (DP) is employed to find the global optimal solution. Thirdly, for practical implementation, NMPC-based control strategy is developed, where the cost function design and weights calibration are done in comparison with DP global optimal solution. Weight-tuning results show that our NMPC-based approach can achieve close driving range maximization as compared to the DP benchmark while ensuring cabin comfort. The developed NMPC-based ITM strategy is further illustrated by comparing its performance to two additional benchmark strategies, i.e., rule-based control and cabin heating only. Finally, our simulation results also identify several important factors that impact the benefits of the proposed NMPC-based ITM, which are used to summarize the operating conditions under which the proposed ITM is critically needed.