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Maintaining the fuel temperature and fuel system components below certain values is an important design objective. Predicting these temperatures is therefore one of the key parts of the vehicle’s thermal management process. One of the physical processes affecting fuel tank temperature is fuel vaporization, which is controlled by the vapor pressure in the tank, fuel composition and fuel temperature. Models are developed to enable the computation of the fuel temperature, fuel vaporization rate in the tank, fuel temperatures along the fuel supply lines, and follow its path to the charcoal canister and into the engine intake. For diesel fuel systems where a fuel return line is used to return excess fluid back to the fuel tank, an energy balance will be considered to calculate the heat added from the high-pressure pump and vehicle under-hood and underbody.

In this paper we present an integrated approach which combines analysis of the effect of simultaneous variations in model input parameters on component or system temperatures. The sensitivity analysis can be conducted by varying model input parameters using specific values that may be of interest to the user. The alternative approach is to use a structured set of parameters generated in the form of a DFSS DOE matrix. The matrix represents a combination of simulation conditions which combine the control factors (CF) and noise factors. CF’s are the design parameters that the engineer can modify to achieve a robust design. Noise factors include parameters that are outside the control of the design engineer. In automotive thermal management, noise factors include changes in ambient temperature, exhaust gas temperatures or aging of exhaust system or heat shields for example.

Engine mount is one of the temperature sensitive components in the vehicle under-hood. Due to increasing requirements for improved fuel economy, the under-hood thermal management has become very challenging in recent years. In order to study the effects of material thermal degradation on engine mount performance and durability; it is required to estimate the temperature of engine mount rubber during various driving conditions. The effect of temperature on physical properties of natural rubber can then be evaluated and the life of engine mount can be estimated. In this paper, a bench test is conducted where the engine mount is exposed to a step change in the environment around it, and the temperature of the rubber section is recorded at several points till a steady state temperature is reached. A time response curve is generated, from which a time constant is determined.

One of the key inputs 1-D transient simulation takes is a detailed front end cooling flow map. These maps that are generated using a full vehicle Three-dimensional Computational Fluid Dynamics (3D CFD) model require expensive computational resources and time. This paper describes how an adaptive sampling of the design space allowed the reduction of computational efforts while keeping desired accuracy of the analysis. The idea of the method was to find a pattern of Design of Experiments (DOE) sampling points for 3D CFD simulations that would allow a creation of an approximation model accurate enough to predict output parameter values in the entire design space of interest. Three procedures were implemented to get the optimal sampling pattern.

A large amount of heat is generated in electric vehicle battery packs during high rate charging, resulting in the need for effective cooling methods. In this paper, a prototype liquid cooled large format Lithium-ion battery module is modeled and tested. Experiments are conducted on the module, which includes 31Ah NMC/Graphite pouch battery cells sandwiched by a foam thermal pad and heat sinks on both sides. The module is instrumented with twenty T-type thermocouples to measure thermal characteristics including the cell and foam surface temperature, heat flux distribution, and the heat generation from batteries under up to 5C rate ultra-fast charging. Constant power loss tests are also performed in which battery loss can be directly measured.

The demand for vehicles with electrified powertrain systems is increasing due to government regulations on fuel economy. The battery systems in a PHEV (Plug-in Hybrid-electric Vehicle) have achieved tremendous efficiency over past few years. The system has become more delicate and complex in architecture which requires sophisticated thermal management. Primary reason behind this is to ensure effective cooling of the cells. Hence the current work has emphasized on developing a “Physics based” thermal management modeling framework for a typical battery system. In this work the thermal energy conservation has been analyzed thoroughly in order to develop necessary governing equations for the system. Since cooling is merely a complex process in HEV battery systems, the underlying mechanics has been investigated using the current model. The framework was kept generic so that it can be applied with various architectures. In this paper the process has been standardized in this context.

More stringent Federal emission regulations and fuel economy requirements have driven the automotive industry toward more efficient vehicle thermal management systems to best utilize the heat produced from burning fuel and improve driveline efficiency. The greatest part of the effort is directed toward the hybridization of automotive transmission systems. The efficiency and durability of hybrid powertrain depends on the heat generation in electric motors and their interactions among each other, ambient condition, the cooling system and the transmission component configuration. These increase the complexity of motor temperature prediction as well as the computational cost of running a conjugate heat-transfer based CFD analysis. In this paper, 1D physics based thermal model is developed which allows rapid and accurate component-wise temperature estimation of the electric motor during both steady-state and transient driving cycles.

The key hurdles to achieving wide consumer acceptance of battery electric vehicles (BEVs) are weather-dependent drive range, higher cost, and limited battery life. These translate into a strong need to reduce a significant energy drain and resulting drive range loss due to auxiliary electrical loads the predominant of which is the cabin thermal management load. Studies have shown that thermal sub-system loads can reduce the drive range by as much as 45% under ambient temperatures below −10 °C. Often, cabin heating relies purely on positive temperature coefficient (PTC) resistive heating, contributing to a significant range loss. Reducing this range loss may improve consumer acceptance of BEVs. The authors present a unified thermal management system (UTEMPRA) that satisfies diverse thermal and design needs of the auxiliary loads in BEVs.

More stringent federal emission regulations and fuel economy requirements have driven the automotive industry toward more sophisticated vehicle thermal management systems in order to best utilize the waste heat and minimize overall power consumption. With all new technologies and requirements, how to properly design, optimize, and control the vehicle thermal and cooling systems become great challenges to automotive engineers. Model based approach has become essential to the new thermal management system architectures design and evaluation of the optimal system solutions. This paper will discuss how the model based vehicle thermal system simulation tools have been developed from analytical & empirical data, and have been used for assessment and development of new thermal management system architectures.

Due to ever-tightening CO2 regulations on passenger vehicles, it is necessary to find novel methods to improve powertrain system efficiency. These increases in efficiency should generally be cost effective so that the customer perceives that they add value. One approach for improving system efficiency has been the use of thermal energy management. For example, changing the flow of, or reusing “waste” heat from the powertrain to improve efficiency. Due to the interactions involved with thermal management, a system level approach is useful for exploring, selecting, and developing alternative solutions. It provides a structured approach to augment the right kind of synergies between subsystems and mitigate unintended consequences. However, one challenge with using these approaches early in a program is having appropriate metrics for assessing key aspects of the system behaviors.

With the demand of growing cooling requirements of fast charging and new thermal architecture design in battery electric vehicles, the automotive industry is exploring electric compressors of large displacement. Compared with small and mid-size (displacement less than 33 cc) compressor, large (34-44 cc) and extra-large (45 cc and above) compressor products are used. This paper investigates the compressor sizing effect for heat pump (HP) system of A-Segment and D-Segment battery electric vehicles. The system performance is evaluated with large (34 cc) and extra-large (57 cc) compressors by considering energy efficiency, cabin thermal management and battery fast charging use cases.

Thermal management of lithium-Ion battery (LIB) has become very critical issue in recent years. One of the challenges for the design and packaging of the battery is to maintain the battery temperature within acceptable ranges and also reduce temperature gradients within the battery cells. Controlling the battery temperature is essential for the battery performance and the long-term battery life. Increased difference between battery cell temperatures can lead to non-uniform charging and non-uniform ageing of battery cells. The purpose of this paper is to investigate available technologies using heat pipes as a means of improving battery thermal management. Several studies have been conducted regarding the effect of heat pipes on battery temperature. However, in this paper we present a comprehensive study of heat pipes effects through transient analysis of a complete vehicle thermal model.

Lead-acid batteries have been widely used in automotive applications. Extending battery life and reducing battery warranty requires reducing any deteriorating to battery internals and battery electrolyte. At the end of battery life, it is required to maintain at least 50% of its initial capacity [1,2]. The rate of battery degradation increases at high battery temperatures due to increased rate of electrochemical reactions and potential loss of battery electrolyte. For Lead-Acid batteries, an electrolyte solution consists of diluted sulfuric acid. Battery electrolyte/water loss affects battery performance. Water loss is caused by high internal battery temperature and gassing off due to battery electrochemistry. High temperatures, high charging rates, and over charging can cause a loss of electrolyte in non-sealed batteries. In sealed batteries, the same factors will cause an increase in temperature and pressure which can eventually result in the release of hydrogen and oxygen gases.

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.

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.

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.

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.

This paper proposes a domain-centralized powertrain E/E (electrical and/or electronic) architecture for all-electric vehicles that features: a powerful master controller (domain controller) that implements most of the functionality of the domain; a set of smart actuators for electric motor(s), HV (High Voltage) battery pack, and thermal management; and a gateway that routes all hardware signals, including digital and analog I/O, and field bus signals between the domain controller and the rest of the vehicle that is outside of the domain. Major functional safety aspects of the architecture are presented and a safety architecture is proposed. The work represents an early E/E architecture proposal. In particular, detailed partitioning of software components over the domain’s Electronic Control Units (ECUs) has not been determined yet; instead, potential partitioning schemes are discussed.