Automotive Climate Control Research Articles

Lateral dispersion in a lattice porous heater core for compact operations

Louvered fin-and-tube cores have been the most popular choice for enhancing the heat transfer performance of compact heat exchangers such as automotive climate control systems (ACCS), because of their moderate heat removal capacity with least pressure drop compared to other heat exchanger core elements. However, their performance in such systems is debilitated if the incident coolant stream is highly non-uniform due to lateral blockage of flow by the fins resulting from compactness of the overall system. This study demonstrates how such lateral blockage imposed by a conventional louvered fin-and-tube core can be relieved by a “lattice porous core” which induces three-dimensional momentum/thermal dispersion within the core under non-uniform incident coolant streams. Especially under the highly localized non-uniform distribution of coolant streams found in a typical ACCS, the lattice porous core thermally outperforms the conventional core by up to 35% within its typical operational range.

Online prediction of time series with assumed behavior

The prediction of future time series values is essential for many fields and applications. In some settings, the time series behavior is expected to follow distinct patterns which in turn may change over time due to a change in the user’s preferences/behavior or a change in the environment itself. In this article, we propose to leverage the assumed time series behavior by developing specialized novel online machine learning algorithms. To demonstrate the potential benefits of our approach compared to existing practices we focus on two commonly assumed time series behaviors: exponential decay and sigmoidal. We present two innovative online learning algorithms, Exponentron for the prediction of exponential decay time series and Sigmoidtron for the prediction of sigmoidal time series. We provide an extensive evaluation of both algorithms both theoretically and empirically using synthetic and real-world data. Our results show that the proposed algorithms compare favorably with the classic time series prediction methods commonly deployed today by providing a substantial improvement in prediction accuracy. Furthermore, we demonstrate the potential applicative benefit of our approach for the design of a novel automated agent for the improvement of the communication process between a driver and its automotive climate control system. Through an extensive human study with 24 drivers we show that our agent improves the communication process and increases drivers’ satisfaction.

Off-design performance of a louvered fin-tube heater core in an automotive climate control system

Louvered fin-and-tube heat exchanger cores, operating inside of an automotive climate control system (ACCS), are used to control temperature and humidity in a passenger cabin. The thermal performance of these cores is typically sensitive to flow features inside the core, which have been well studied for uniform flow fields as well as some non-uniform and inclined flow-fields upstream of the core. The compact geometry of an ACCS unit results in the flow-fields upstream of the core being different from those used in previous studies. When measuring the performance of a louvered fin-and-tube heater core inside a commercially manufactured ACCS unit, up to a 60% reduction in the core’s thermal performance compared to the performance when exposed to a uniform upstream flow is detected. Such a drastic performance reduction has not been reported in the literature. As such a systematic breakdown is made to elaborate how some key and specific ACCS unit features designed for the sake of compactness could play a detrimental role in reducing the overall thermal performance of a given louvered fin-and-tube heater core. By mimicking the actual ACCS features the performance deterioration in the commercial unit could be largely replicated. The individual contributing effects of the various fluidic features such as flow separation and recirculation are determined. Only 50% of the measured 60% deterioration, however, could be accounted for, suggesting that other ACCS unit properties not assessed in detail in this study may also adversely affect the core’s performance.

Extended Range Electric Vehicle With Driving Behavior Estimation in Energy Management

Battery and energy management methodologies have been proposed to address the design challenges of driving range and battery lifetime in electric vehicles (EVs). However, the driving behavior is a major factor which has been neglected in these methodologies. In this paper, we propose a novel context-aware methodology to estimate the driving behavior in terms of future vehicle speeds and integrate this capability into EV energy management. We implement a driving behavior model using a variation of artificial neural networks called nonlinear autoregressive model with eXogenous inputs (NARX). We train our novel context-aware NARX model based on historical behavior of real drivers, their recent driving reactions, and route average speed retrieved from Google Maps in order to enable driver-specific and self-adaptive driving behavior modeling and long-term estimation. We analyze the estimation error of our methodology and its impact on a battery lifetime-aware automotive climate control, comparing to the state-of-the-art methodologies for various estimation window sizes. Our methodology shows only 12% error for up to 30-s speed prediction which is an improvement of 27% compared to the state-of-the-art. Therefore, the higher accuracy helps the controller to achieve up to 82% of the maximum energy saving and battery lifetime improvement achievable in ideal methodology where the future vehicle speeds are known.

Design and Analysis of Battery-Aware Automotive Climate Control for Electric Vehicles

Electric Vehicles (EV) as a zero-emission means of transportation encounter challenges in battery design that cause a range anxieties for the drivers. Besides the electric motor, the Heating, Ventilation, and Air Conditioning (HVAC) system is another major contributor to the power consumption that may influence the EV battery lifetime and driving range. In the state-of-the-art methodologies for battery management systems, the battery performance is monitored and improved. While in the automotive climate control, the passenger’s thermal comfort is the main objective. Hence, the influence of the HVAC power on the battery behavior for the purpose of jointly optimized battery management and climate control has not been considered. In this article, we propose an automotive climate control methodology that is aware of the battery behavior and performance, while maintaining the passenger’s thermal comfort. In our methodology, battery parameters and cabin temperature are modeled and estimated, and the HVAC utilization is optimized and adjusted with respect to the electric motor and HVAC power requests. Therefore, the battery stress reduces, while the cabin temperature is maintained by predicting and optimizing the system states in the near-future. We have implemented our methodology and compared its performance to the state-of-the-art in terms of battery lifetime improvement and energy consumption reduction. We have also conducted experiments and analyses to explore multiple control window sizes, drive profiles, ambient temperatures, and modeling error rates in the methodology. It is shown that our battery-aware climate control can extend the battery lifetime by up to 13.2% and reduce the energy consumption by up to 14.4%.

On human–machine relations

This paper presents an approach to human---machine interactions based on the concept of teamwork and the psychological theory of object relations. We envision the human and the machine in a close relationship that has many aspects of human-to-human relations. Not only does the machine have to relate to and accommodate human wants and needs, but also, to some extent, the human is called to reciprocate. We propose a framework consisting of eleven attributes that describe generic processes in teamwork: commitment, goal definition, common ground, belief, planning, transparency, sensitivity, caring, responsibility, trust, and reflection. Using an automotive climate control system as an example, we show how some of these attributes can be used to evaluate user interactions and point to new design opportunities. Based on results from a pilot study of driver interaction with the climate control system, we operationalized sensitivity and caring for other team members, encapsulated them in a computational architecture, and implemented a control interface. The evaluation of the control interface during a driving experiment suggests that it is markedly better than a regular interface and is almost as good as a human expert who interacts with the climate control system in response to the driver's needs and wants.

Potential energy consumption reduction of automotive climate control systems

In recent years fuel consumption of passenger vehicles has received increased attention by customers, the automotive industry, regulatory agencies and academia. One area which affect the fuel consumption is climate control systems.Twenty-one energy saving measures were evaluated regarding the total energy use for vehicle interior climate using simulation. Evaluated properties were heat flow into the passenger compartment, electrical and mechanical work. The simulation model included sub models of the passenger compartment, air-handling unit, Air Conditioning (AC) system, engine and engine cooling system. A real-world representative test cycle, which included tests in cold, intermediate and warm conditions, was used for evaluation.In general, few single energy saving measures could reduce the energy use significantly. The measures with most potential were increased blower efficiency with a reduction of 46% of the electrical work and increased AC-system disengage temperature with a reduction of 27% of the mechanical work. These results show that the operation of the climate control system had a large effect on the energy use, especially compared to the required heating and cooling of the passenger compartment. As a result energy saving measures need to address how heating and cooling is generated before reducing the heat flow into the passenger compartment.

An automated approach to quantifying functional interactions by mining large-scale product specification data

ABSTRACTThe authors of this work hypothesise that the semantic relationship between modules' functional descriptions is correlated with the functional interaction between the modules. A deeper comprehension of the functional interactions between modules enables designers to integrate complex systems during the early stages of the product design process. Existing approaches that measure functional interactions between modules rely on the manual provision of designers' expert analyses, which may be time consuming and costly. The increased quantity and complexity of products in the twenty-first century further exacerbates these challenges. This work proposes an approach to automatically quantify the functional interactions between modules, based on their textual technical descriptions. Compared with manual analyses by design experts who use traditional design structure matrix approaches, the text-mining-driven methodology discovers similar functional interactions, while maintaining comparable accuracies. The case study presented in this work analyses an automotive climate control system and compares the functional interaction solutions achieved by a traditional design team with those achieved following the methodology outlined in this paper.

Aero‐acoustic predictions of automotive dashboard HVAC (heating, ventilating, and air‐conditioning ducts).

The flow‐induced noise generated by automotive climate control systems is today emerging as one of the main noise sources in a vehicle interior. Numerical simulation offers a good way to analyze these mechanisms and to identify the aerodynamic noise sources in an industrial context driven by permanent reduction in programs timing and development costs, implying no physical prototype of ducts before serial tooling. This paper focuses on a numerical aeroacoustic study of automotive instrument panel ducts to estimate the sound produced by the turbulent flow. The methodology is the following: the unsteady‐flow field is first computed using a CFD solver—here FLUENT. Then, the acoustic finite element solver ACTRAN computes the acoustic sound sources from these time domain CFD results. The sources are finally propagated into the vehicle interior in the frequency domain. One advantage of the technique is that the CFD computations are completely separated from the acoustic computations. This allows reusing one CFD computation for many different acoustic computations. The theoretical background is presented in the first sections of this paper. Then, the accuracy of the method for real industrial cases is demonstrated by comparing the numerical results to experimental results available at VISTEON.

自動車用空調機器の技術開発今後の展望(<特集>乗り物の未来像)

自動車用空調機器の技術開発今後の展望(<特集>乗り物の未来像)

Toward simulation-based design

This paper discusses the technologies needed to support the application of simulation-based design. Emphasis is placed on the technical components that must be added to existing CAD and CAE tools to enable the application of simulation-based design. These components include a simulation model manager, simulation data manager, adaptive control tools and simulation model generators. The application of these technologies to automotive climate control system design is demonstrated.

ANALYSIS AND DESIGN OF MUFFLERS—AN OVERVIEW OF RESEARCH AT THE INDIAN INSTITUTE OF SCIENCE

The reciprocating motion of the piston(s) of engines and compressors and the associated intake and discharge of gases are responsible for noise radiation to the atmosphere that ranks as a major pollutant of the urban environment. Mufflers have been developed over the last seventy years based on electro–acoustic analogies and experimental trial and error. Passive mufflers based on impedance mismatch, called reflective or reactive mufflers, have been most common in the automobile industry. Mufflers based on the principle of conversion of acoustic energy into heat by means of highly porous fibrous linings, called dissipative mufflers or silencers, are generally used in heating, ventilation and air-conditioning systems. The author has been working in this area for over 27 years. Of late, he has been researching in the vibro–acoustics of hoses used in automotive climate control systems. The present paper gives an overview of the research findings of the author and his students in different aspects of active as well as passive mufflers in the last decade. The same are related to the contemporary state of the art. Finally, areas needing further research are indicated.

Prediction of the vibro-acoustic transmission loss of planar hose-pipe systems

Vibro-acoustic energy travels through hose walls as longitudinal waves and flexural waves, apart from the sound waves through the fluid medium inside. Longitudinal waves in the hose wall are coupled to the sound waves inside by means of the hose-wall Poisson’s ratio. Both in turn get coupled to bending or flexural waves because of the energy transfer or interaction at the bends. For any of these three types of waves incident on one end of a hose, waves of all the three types may be transmitted on the other end because of their dynamical coupling with one another. Therefore, in the present paper, expressions have been derived for the 3×3 transmission loss matrix for a two-dimensional or planar piping system in terms of elements of the overall 8×8 transfer matrix of the system. These expressions have then been used in a comprehensive computer program to evaluate the vibro-acoustic performance of hoses, with particular application to the automotive climate control systems with gaseous as well as liquid media. Finally, parametric studies have been made that have led to some general design guidelines.

Recognition of Automotive Climate Control Symbols

One Hundred Ninety Six automobile buyers were surveyed in Chicago, Illinois to determine user understanding of symbols and words commonly found on climate (heater and air conditioning) controls in today's automobiles. This survey was part of a larger market research project. Subjects were administered a paper and pencil test and were asked to identify symbols and words randomly located on a page by recording their answers on a blank line beside the symbol. They were then asked to operate climate controls labeled either with words or symbols following which they rated the ease of identifying the controls. The buyer population that was surveyed contained primarily import car buyers due to the nature of the product being researched. Recognition rates ranged from 92% to 47%, indicating that most of the symbols were relatively well understood except for the rear defrost, air conditioning, and defrost/floor air flow symbols. However, subjects also responded that words were preferred over symbols in ease of identifying functions by almost a 2 to 1 margin in preference except for the air distribution modes, where symbols were preferred over words 61% to 48%.

Automotive climate control

This paper deals with automotive climate control using modern control theory. Automobile compartment temperature is controlled by varying compressor capacity and the position of the air mixing damper. The mathematical model of the system is obtained using a statistical identification method, and this system model is reduced to lower order using minimal realization. The experimental results show robust control performance under climate changes causing parameter variations or disturbances.