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Spray impingement is an important phenomenon that introduces turbulence into the spray that promotes fuel vaporization, air entrainment and flame propagation. However, liquid impingement on the surface leads to wall-wetting and film deposition. The film region is a fuel-rich zone and it has potentials to produce higher emission. Film deposition in a non-reacting spray was studied previously but not in a reacting spray. In the current study, the film deposition of a reacting diesel spray was studied through computational fluid dynamic (CFD) simulations under a variety of ambient temperatures, gas compositions and impinging distances. Characteristics of film mass, distribution of thickness, soot formation and temperature distributions were investigated. Simulation results showed that under the same impinging distance, higher ambient temperature reduced film mass but showed the same liquid film pattern.

In this paper we investigate the application of time constant to estimate the external heat transfer coefficient (h) around specific vehicle components. Using this approach, a test sample in the form of a steel plate is placed around the component of interest. A step change is applied to air temperature surrounding the sample. The response of the sample temperature can be analyzed and the heat transfer coefficient can therefore be calculated. Several test samples were installed at several locations in the vehicle under-hood and underbody. A series of vehicle tests were designed to measure the time constant around each component at various vehicle speeds. A correlation between estimated heat transfer coefficients and vehicle speed was generated. The developed correlations and the measured component ambient temperatures can be readily used as input for thermal simulation tools. This approach can be very helpful whenever CFD resources may not be available.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

Automotive Heating Ventilation and Air Conditioning (HVAC) system is essential in providing the thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in IC engine vehicles, is considered to be one of the dominant sources inside the electric vehicle cabin. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path using virtual tools during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, noise simulations were carried-out with ducts and registers. A Finite Volume Method (FVM) based 3-dimensional (3D) Computational Fluid Dynamics (CFD) solver was used for flow as well as acoustic simulations.

Electrified powertrains will play a growing role in meeting global fuel consumption and CO2 requirements. In support of this, FCA US has developed its first dedicated hybrid transmission (the eFlite® transmission), used in the Chrysler Pacifica Hybrid. The Chrysler Pacifica is the industry’s first electrified minivan. [2] The new eFlite hybrid transmission architecture optimizes performance, fuel economy, mass, packaging and NVH. The transmission is an electrically variable FWD transaxle with an input split configuration and incorporates two electric motors, both capable of driving in EV mode. The lubrication and cooling system makes use of two pumps, one electrically operated and one mechanically driven. The Chrysler Pacifica has a 16kWh lithium ion battery and a 3.6-liter Pentastar® engine which offers total system power of 260 hp with 84 MPGe, 33 miles of all electric range and 566 miles total driving range. [2] This paper’s focus is on the eFlite transmission.

Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin’s minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude.

SUV Aerodynamics has received increased attention as the stake this segments holds in the automotive market keeps growing year after year, as well as its direct impact on fuel economy. Understanding the key physics in order to accomplish both fuel efficient and aesthetic products is paramount, which indeed gave origin to a major initiative to foster collaborative aerodynamic research across academia and industry, the so-called DrivAer model. In addition to this sedan-based model, a new dedicated SUV generic model, called AeroSUV [1], has been introduced in 2019, also intended to provide a common framework for aerodynamic research for both experimental work and numerical simulation validation. The present paper provides an area of common ground for SUV bodywork design focused on aerodynamic drag reduction by investigating both Estate and Fast back configurations of the generic AeroSUV model.

More stringent Federal emission regulations and fuel economy requirements have driven the automotive industry towards more sophisticated vehicle thermal management systems to best utilize the waste heat and improve driveline efficiency. The final drive unit in light and heavy duty trucks usually consists of geared transmission and differential housed in a lubricated axle. The automotive rear axle is one of the major sources of power loss in the driveline due to gear friction, churning and bearing loss affecting vehicle fuel economy. These losses vary significantly with lubricant viscosity. Also the temperatures of the lubricant are critical to the overall axle performance in terms of power losses, fatigue life and wear. In this paper, a methodology for modeling thermal behavior of automotive rear axle with heat exchanger is presented. The proposed model can be used to predict the axle lubricant temperature rise.

This paper describes the design, development, and operation of a rear axle dual-shell heat exchanger on the RAM 1500 Light Duty truck. This system has been proven to increase fuel economy and reduce exhaust emissions, particularly CO2, on the EPA Cold City schedule. The energy conversion strategy was first explored using math modeling. A PUGH analysis associated with concept selection is included. To refine the hardware and develop a control strategy prior to testing, a portable flow cart was developed to assess system performance and to correlate the multi-node heat transfer model. Bench testing focused on the durability and functional aspects of integrating the dual-shell axle cover with the axle and coolant delivery system through a comprehensive design and validation plan. Vehicle testing included various fuel economy and emissions related driving schedules to quantify the benefits.

Thermal development of automotive applications is a lot more complex than it used to be in the past. Specifically, for Plug-in Hybrid Electric Vehicles (PHEVs), all the sub-systems are so intertwined that it’s hard to analyze them as sub-systems only. A system level solution is needed for proper sizing of components. For early thermal development, a co-simulation method can ensure that we take into account the inter-dependency of all the thermal features in the car. As for example, a large PHEV battery may need to be passively cooled by refrigerant, which is also associated with the interior Heating, Ventilation, and Air Conditioning (HVAC) cooling system. For proper sizing of the condenser, chiller etc., one has to account for the battery cooling and cabin cooling as one system. There are also many thermal actuators on a PHEV, e.g. control valves, pulse-width-module (PWM) pumps, electric compressor, electric coolant heaters etc.

Automotive exhaust noise is one of the major sources of noise pollution and it is controlled by passive control system (mufflers) and active control system (loudspeakers and active control algorithm). Mufflers are heavy, bulky and large in size while loudspeakers have a working temperature limitation. Carbon nanotube (CNT) speakers generate sound due to the thermoacoustic effect. CNT speakers are also lightweight, flexible, have acoustic and light transparency as well as high operating temperature. These properties make them ideal to overcome the limitations of the current exhaust noise control systems. An enclosed, coaxial CNT speaker is designed for exhaust noise cancellation application. The development of a 3D multi-physics (coupling of electrical, thermal and acoustical domains) model, for the coaxial speaker is discussed in this paper. The model is used to simulate the sound pressure level, input power versus ambient temperature and efficiency.

Electric motor performance is primarily limited by the amount of heat that can be effectively dissipated. Recent developments in electric motor thermal management have been employing direct oil spray/splash based cooling for improved performance. Simulation of two phase (air and oil) flow and associated heat transfer for such applications has been computationally challenging, hence not fully explored in the literature. This paper describes a numerical study in which two phase flow and heat transfer within a direct-oil-cooled electric motor are analyzed using CFD software. A detailed temperature field of all the motor components under different operating conditions is generated using a conjugate heat transfer approach. Numerical results are compared with the temperature measurements at discrete locations in motor.

There are a variety of test protocols associated with vehicle fuel economy and emissions testing. As a result, a number of test protocols currently exist to measure axle efficiency and spin loss. The intent of this technical paper is to describe a methodology that uses a singular axle efficiency and spin loss procedure. The data can then be used to predict the effects on vehicle FE and GHG for a specific class of vehicles via simulation. An accelerated break-in method using a comparable energy approach has been developed, and can be used to meet the break-in requirements of different vehicle emission test protocols. A “float to equilibrium” sump temperature approach has been used to produce instantaneous efficiency data, which can be used to more accurately predict vehicle FE and GHG, inclusive of Cold CO2. The “Float to Equilibrium” approach and “Fixed Sump Temperature” approach has been compared and discussed.

Cooling airflow is an essential factor when it comes to vehicle performance and operating safety. In recent years, significant efforts have been made to maximize the flow efficiency through the heat exchangers in the under-hood compartment. Grille shutters, new fan shapes, better sealings are only some examples of innovations in this field of work. Underhood cooling airflow simulations are an integral part of the vehicle development process. Especially in the early development phase, where no test data is available to verify the cooling performance of the vehicle, computational fluid dynamics simulations (CFD) can be a valuable tool to identify the lack of fan performance and to develop the appropriate strategy to achieve airflow goals through the heat exchangers. For vehicles with heat exchangers in the underhood section the airflow through those components is of particular interest.

Approximately ninety percent of automotive wind tunnels in the world have incorporated or been built with a Moving Ground Plane (MGP). However, very little research has been published in the literature on the interaction of the MGP and the vehicle. The goal of this paper is to characterize the flow structures and unsteady motion of the isolated wheel wake and its interaction with a 5-belt MGP using numerical simulations. This paper is divided into three parts. In the first part, a Computational Fluid Dynamics (CFD) study is carried out on the Mears (2004) wheel using IDDES model where the CFD process to be used later is validated against the experimental data. In the second part, a simulation is carried out for a 5-belt MGP system and the verification is carried out using the Von Karman integral formula for the boundary layer development over the belts.

Stringent requirements for high fuel economy and energy efficiency mandate using increasingly complex vehicle thermal systems in most types of electrified vehicles (xEVs). Enabling the maximum benefits of such complex thermal systems under the full envelope of their operating modes demands designing complex thermal control systems. This is becoming one of the most challenging problems for electrified vehicles. Typically, the thermal systems of such vehicles have several modes of operation, constituting nonlinear multiple-input/multiple-output (MIMO) dynamic systems that cannot be efficiently controlled using classical or rule based strategies. This paper covers the different steps towards the design of a model-based control (MBC) strategy that can improve the overall performance of xEV thermal control systems. To achieve the above objective, the latter MBC strategy is applied to control cooling of the cabin and high voltage battery.

In this paper, a control strategy for state of charge (SOC) allocation using navigation data for Hybrid Electric Vehicle (HEV) propulsion systems is proposed. This algorithm dynamically defines and adjusts a SOC target as a function of distance travelled on-line, thereby enabling proactive management of the energy store in the battery. The proposed approach incorporates variances in road resistance and adheres to geolocation constraints, including ultra-low emission zones (uLEZ). The anticipated advantages are particularly pronounced during scenarios involving extensive medium-to-long journeys characterized by abrupt topological changes or the necessity for exclusive electric vehicle (EV) mode operation. This novel solution stands to significantly enhance both drivability and fuel economy outcomes.