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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.

In this paper, a comparison between different six-phase machine topologies is conducted considering their technical performance for automotive applications. Asymmetrical and symmetrical configurations, as well as neutral point connection, are considered as candidate topologies and modelled using vector space decomposition (VSD) and double stator or double dq transformations. In both cases, a generalized model to include an arbitrary phase shift between the windings is presented as well as the effect of the neutral connection on the inverter model. For the selection, the steady-state and post-fault performance are considered in terms of control flexibility, fault-tolerant capability, and dc-link voltage utilization. For the latest, the different topologies are evaluated operating in both linear and overmodulation regions based on space vector modulation (SVM).

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.

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

During driving conditions, when it is needed to transition from Electric Vehicle (EV) to Hybrid Vehicle operation, synchronization of the engine with the shaft and transmission is essential to enable clutch engagement and, subsequently, providing engine power to the wheels. Challenges arise when the engine must generate power to move itself and cannot rely on electric motors for precision. Cost-effective hybrid vehicle propulsion architectures which utilize small 12V belt-starter generators (BSGs) to initiate engine activation are inherently affected. In these situations, a speed profile that balance rapid response and control effort while considering system limitations to mitigate undesirable overshoots and delays, is required. This paper presents a Linear Quadratic Integral (LQI) approach to formulate a speed reference profile that ensures optimal engine behavior.

In this paper, a mild hybrid drive train has been proposed. A small electric motor with low rated voltage (42 V) is used to (1) propel the vehicle at low speed, (2) replace the fluid-coupled torque converter and (3) realize regenerative braking. With proper design and control, the fuel economy in urban driving can be significantly improved without much change from conventional drive train to the mild hybrid drive train.

Significant amount of energy is lost in frequent braking, automatic transmission and engine idling for a conventional engine powered passenger car while driving in cities. In this paper, a mild hybrid vehicle drive train has been introduced. It uses a small electric motor with floating stator, called TRANSMOTOR and small and a battery pack. The transmotor functions as a generator, engine starter, frictionless clutch (electric torque coupler), regenerative braking and propelling. The mild hybrid drive train can effectively reduce the urban-driving fuel consumption by regenerative braking, eliminate of energy losses in conventional automatic transmission and engine idling. The drive train can use low voltage system (42V for example), due to the low electric power rating, and is more similar to conventional drive train than full hybrid vehicle. Therefore, less effort is needed to evolve it from conventional vehicles.

Understanding planetary gear efficiency is more involved than understanding efficiency of external gears because of the recirculating power that is inherent in planetary gear operation. There have been several publications going back several decades on this topic. However, many of these publications are mathematical in their approach and tend to be overlooked by practicing engineers. This paper brings a new, more visual and more intuitive approach to the problem. It uses lever diagrams, which have been a standard tool in the transmission engineer’s arsenal for almost four decades, to visualize the power flow and develop analytical expressions for the efficiency of simple and compound planetary gears. It then extends the approach to more complex gear trains.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

In recent decades, there has been a growing focus on improving overall vehicle efficiency and fuel economy due to growing customer awareness and more stringent environmental regulations. Effort has been placed on improving the engine efficiency and reducing the losses of the transmission and driveline. One essential component of this process is to correctly size the transmission oil pump as it is one of the main energy consumers in the powertrain. Conversely, the oil pump has a critical mission of ensuring reliable and high quality gear shift as well as supplying lubrication and cooling oil to various components in the transmission. This paper outlines a strategy to systematically understand and quantify the main requirements for sizing the oil pump to ensure adequate performance while minimizing the energy consumption of the pump. The proposed framework is a three-legged approach.

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.

A turbocharger is currently widely used to boost performance of an internal combustion engine. Generally, a turbocharger consists of a compressor which typically is driven by an exhaust turbine. The compressor will influence how the low frequency engine pulsation propagates in the intake system. The compressor will also produce broad-band flow induced sound due to the turbulence flow and high frequency narrowband tonal sound which is associated with rotating blade pressures. In this paper, a practical simulation procedure based on a computational fluid dynamics (CFD) approach is developed to predict the flow induced sound of a turbocharger compressor. In the CFD model of turbocharger compressor, the unsteady, moving wheel, detached eddy simulation (DES) approach are utilized. In this manner, both the broad-band and narrow-band flow induced sound are directly resolved in the CFD computation.

Rapid Compression Machines (RCM) offer the ability to easily change the compression ratio and the pressure/mixture composition/temperature to gather ignition delay data at various engine relevant conditions. Therefore, RCMs with optical access to the combustion chamber can provide an effective way to analyze macroscopic spray characteristics needed to understand the spray injection process and for spray model development, validation and calibration at conditions that are suitable for engines. Fuel surrogates can help control fuel parameters, develop models for spray and combustion, and perform laser diagnostics with known fluorescence characteristics. This study quantifies and evaluates the macroscopic spray characteristics of multicomponent gasoline surrogates in comparison to their gasoline counterparts, under gasoline direct injection (GDI) engine conditions.

In this work autoignition delay times of two multi-component surrogates (high and low RON) were experimentally compared with their target full blend gasoline fuels. The study was conducted in a rapid compression machine (RCM) test facility and a direct test chamber (DTC) charge preparation approach was used for mixture preparation. Experiments were carried over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. Dilution in the reactant mixture was varied from 0% to 30% CO2 (by mass), with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy emulates exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines. The multicomponent surrogate captured the reactivity trends of the gasoline-air mixtures reasonably well in comparison to the single component (iso-octane) surrogate.

As engines are equipped with an increased number of control actuators to meet fuel economy targets they become more difficult to control and calibrate. The large number of control actuators encourages the investigation of physics-based control strategies to reduce calibration time and complexity. Of particular interest is spark timing control and calibration since it has a significant influence on engine efficiency, emissions, vibration and durability. Spark timing determination to achieve a desired combustion phasing is currently an empirical process that occurs during the calibration phase of engine development. This process utilizes a large number of stored surfaces and corrections to account for the wide range of operating environments and conditions that a given engine will experience. An obstacle to realizing feedforward physics-based combustion phasing control is the requirement for an accurate and fast combustion model.

The rotary-vee engine is a novel and unusual internal combustion engine. The rotary-vee engine is unique in that all of the components have rotary motion, but the combustion chamber and piston design is similar to a reciprocating engine. Of particular significance, the rotary-vee engine design includes pistons with rings to accomplish the sealing of the combustion chamber. Thus, the rotary-vee engine may offer the sealing benefits of the conventional piston engine, and the vibration and balance characteristics of a rotary engine. This paper includes a review of rotary engines, and places the rotary-vee engine in the context of all rotary engines. In addition, a thermodynamic analysis of the operation of a rotary-vee engine is reported. The rotary-vee engine possesses some advantages relative to other rotary engine designs such as piston ring sealing, and the thermodynamic analysis indicates similar performance as compared to conventional reciprocating engines.

Reducing emissions and the carbon footprint of our society have become imperatives requiring the automotive industry to adapt and develop technologies to strive for a cleaner sustainable transport system and for sustainable economic prosperity. Electrified hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and range extender powertrains provide potential solutions for reducing emissions, but they present challenges in terms of thermal management. A key requirement for meeting these challenges is accurately to predict the thermal loading and temperatures of an internal combustion engine (ICE) quickly under multiple full-load and part-load conditions. Computational Fluid Dynamics (CFD) and thermal survey database methods are used to derive thermal loading of the engine structure and are well understood but typically only used at full-load conditions.

Increase in the atmospheric temperature across the globe during summer, increases the heat load in the vehicle cabin, creating a huge thermal discomfort for the passengers. There are two scenarios where these adverse conditions can be a problem during the summer. Firstly, while driving the vehicle in traffic conditions and secondly, when the vehicle is parked under the sun. When the vehicle is exposed to the radiation from the sun for a period, the cabin temperature can reach alarming levels, which may have serious discomfort and health effects on the people entering the vehicle. Although there are options of remote switching on of air conditioners, they are restricted to vehicles having an automatic transmission and availability of the mobile network. So, it is important to explore the possible options which can be used for restricting the external heat load to the cabin.

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.

This paper discusses a new computer simulation tool, V-Elph, which extends the capabilities of previous modeling and simulation efforts by facilitating in-depth studies of any type of hybrid or all electric configuration or energy management strategy through visual programming and by creating components as hierarchical subsystems which can be used interchangeably as embedded systems. V-Elph is composed of detailed models of four major types of components: electric motors, internal combustion engines, batteries, and vehicle dynamics which can be integrated to simulate drive trains having all electric, series hybrid, and parallel hybrid configurations. V-Elph was written in the Matlab/Simulink graphical simulation language and is portable to most computer platforms. A simulation study of a sustainable, electrically-peaking hybrid-electric vehicle was performed to illustrate the applicability of V-Elph to hybrid and electric vehicle design.