Search Results

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.

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.

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 focuses on the conjugate heat transfer analysis of an I4 engine, and discusses optimization of the coolant passages in engine coolant jackets. Direct Optimization approach integrates an optimizer with the numerical solver. This method of optimization is compared with a metamodel-based optimization in which a metamodel is generated to aid in finding an optimal design. The direct optimization and metamodel approaches are compared in terms of their accuracy, and execution time.

The heat generated by an internal combustion engine must be dissipated to maintain acceptable component temperatures throughout the entire powertrain system under all operating conditions. However, under cold start conditions it is beneficial to retain this available heat to achieve faster warm-up in order to reduce fuel consumption. In modern engines there are several components in the coolant circuit that are used to accelerate the warm-up of sub-system fluids such as the engine oil, transmission oil and axle oil. The magnitude of the fuel consumption reduction will depend on how these rapid warm-up devices are arranged, combined and controlled. This paper describes a methodology that was developed to optimize the distribution of coolant heat in the powertrain system during warm-up. A comparative study can be performed to optimize the arrangement of each heat exchanger in any given powertrain system to minimize cost and time early in development.

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.

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.

Internal combustion engine gets heated up due to continuous combustion of fuel. To keep engine working efficiently and prevent components damage due to very high temperature, the engine needs to be cooled down. Based on power output requirement and provision for cooling system, every engine has it’s unique cooling system. Liquid based cooling systems are majorly implemented in automobile. It’s important to keep in mind that during design phase that, cooling the engine will lower the power to fuel consumption ratio. Therefore, during lower ambient conditions, the cooling system should be able to uniformly increase the temperature of the engine components, engine oil and transmission oil. This is achieved by circulating the coolant through cooling jacket, engine oil heater and transmission oil heater, which will be heated by the combustion heat.

The performance and durability of the lead acid battery is highly dependent on the internal battery temperature. The changes in internal battery temperatures are caused by several factors including internal heat generation and external heat transfer from the vehicle under-hood environment. Internal heat generation depends on the battery charging strategy and electric loading. External heat transfer effects are caused by customer duty cycle, vehicle under-hood components and under-hood ambient air. During soak conditions, the ambient temperature can have significant effect on battery temperature after a long drive for example. Therefore, the temperature rise in a lead-acid battery must be controlled to improve its performance and durability. In this paper a thermal model for lead-acid battery is developed which integrates both internal and external factors along with customer duty cycle to predict battery temperature at various driving conditions.

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.

The trend to simultaneously improve fuel economy and engine performance has led to industry growth of turbocharged engines and as a result, the need to address their undesirable airborne noise attributes. This presents some unique engineering challenges as higher customer expectations for Noise Vibration Harshness (NVH), and other vehicle-level attributes increase over time. Turbocharged engines possess higher frequency noise content compared to naturally aspirated engines. Therefore, as an outcome, whoosh noise in the Air Induction System (AIS) during tip in conditions is an undesirable attribute that requires high frequency attenuation enablers. The traditional method for attenuation of this type of noise has been to use resonators which adds cost, weight and requires packaging space that is often at a premium in the under-hood environment.

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.

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.

Automotive thermal systems are becoming complicated each year. The powertrain efficiency improvement initiatives are driving transmission and engine oil heaters into coolant network design alternatives. The initiatives of electrified and autonomous vehicles are making coolant networks even more complex. The coolant networks these days have many heat exchangers, electric water pumps and valves, apart from typical radiators, thermostat and heater core. Some of these heat exchangers, including cabin heaters deal with very small amount of coolant flow rates at different ambient conditions. This paper describes how viscosity can be a major reason for simulation inaccuracy, and how to deal with it for each component in the coolant network. Both experimental and computational aspects have been considered in this paper with wide range of ambient temperatures.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

Automotive AC systems are typically either single unit or dual unit systems, while the dual unit systems have an additional rear evaporator. The refrigerant evaporates inside these heat exchangers by taking heat and condensing the moisture from the recirculated or fresh air that is being pushed into the car cabin by air blowers. This incoming cold air in turn brings the cabin temperature and humidity to a level that is comfortable for the passengers. These HVAC units have their own thermal expansion valve to set the refrigerant flow, but both are connected to the main AC refrigerant loop. The airflows, however, are controlled independently for front and rear unit that can affect the temperature and amount of air coming into the cabin from each location and consequently the overall cabin cool-down performance.

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.