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One-dimensional single-zone and two-zone analyses have been exercised to calculate the mass fraction burned in an engine operating on ethanol/gasoline-blended fuels using the cylinder pressure and volume data. The analyses include heat transfer and crevice volume effects on the calculated mass fraction burned. A comparison between the two methods is performed starting from the derivation of conservation of energy and the method to solve the mass fraction burned rates through the results including detailed explanation of the observed differences and trends. The apparent heat release method is used as a point of reference in the comparison process. Both models are solved using the LU matrix factorization and first-order Euler integration.

The increased market share of electric vehicles and renewable energy resources have raised concerns about their impact on the current electrical distribution grid. To achieve sustainable and stable power distribution, a lot of effort has been made to implement smart grids. This paper addresses Demand Response (DR) load control in a smart grid using Internet of Things (IoT) technology. A smart grid is a networked electrical grid which includes a variety of components and sub-systems, including renewable energy resources, controllable loads, smart meters, and automation devices. An IoT approach is a good fit for the control and energy management of smart grids. Although there are various commercial systems available for smart grid control, the systems based on open sources are limited. In this study, we adopt an open source development platform named Node-RED to integrate DR capabilities in a smart grid for DR load control. The DR system employs the OpenADR standard.

Technologies that provide potential for significant improvements in engine efficiency include, engine downsizing/downspeeding (enabled by advanced boosting systems such as an electrically driven compressor), waste heat recovery through turbocompounding or organic Rankine cycle and 48 V mild hybridization. FEV’s Integrated Turbocompounding/Waste Heat Recovery (WHR), Electrification and Supercharging (FEV-ITES) is a novel approach for integration of these technologies in a single unit. This approach provides a reduced cost, reduced space claim and an increase in engine efficiency, when compared to the independent integration of each of these technologies. This approach is enabled through the application of a planetary gear system. Specifically, a secondary compressor is connected to the ring gear, a turbocompounding turbine or organic Rankine cycle (ORC) expander is connected to the sun gear, and an electric motor/generator is connected to the carrier gear.

Successive braking of the vehicle, hereinafter referred as brake duty cycle, can elevate the temperature of the brake disc to a very high level. Such high temperatures reached in brake discs can lead to vaporization of the brake fluid if the vehicle is at rest after the brake duty cycle. Excessive temperature operation of the brake disc can also lead to thermal cracks, judder, brake fade, wear and reduce braking effectiveness. Simulation tools can be used to predict the excessive temperature reached during successive braking event. After visualizing the complex flow field over the brake system and analyzing the heat transfer from brake system, simulations can be employed at the early design stage to optimize the design for more airflow over brake discs thus reducing the high temperatures and associated brake fade. In this paper, a CFD model of the vehicle with brake system is coupled with a thermal solver at braking and acceleration velocities.

This paper describes the heat transfer model of a composite aluminum brake rotor and compares the predicted temperatures to dynamometer measurements taken during a 15 fade stop trial. The model is based on meshed surface geometry which is simulated using RadTherm software. Methods for realistically modeling heat load distribution, surface rotation, convection cooling and radiation losses are also discussed. A comparison of the simulation results to the dynamometer data shows very close agreement throughout the fade stop trial. As such, the model is considered valid and will be used for further Steel Clad Aluminum (SCA) rotor development.

The airflow into the engine bay of a passenger car is used for cooling down essential components of the vehicle, such as powertrain, air-conditioning compressor, intake charge air, batteries, and brake systems, before it returns back to the external flow. When the intake ram pressure becomes high enough to supply surplus cooling air flow, this flow can be actively regulated by using arrays of grille shutters, namely active grille shutters (AGS), in order to reduce the drag penalty due to excessive cooling. In this study, the operation of AGS for a generic SUV-type model vehicle is optimized for improved fuel economy on a highway drive cycle (part of SFTP-US06) by using surrogate models. Both vehicle aerodynamic power consumption and under-hood cooling performance are assessed by using PowerFLOW, a high-fidelity flow solver that is fully coupled with powertrain heat exchanger models.

This is the second part of a study on using port water injection to quantifiably enhance the knock performance of fuels. In the United States, the metric used to quantify the anti-knock performance of fuels is Anti Knock Index (AKI), which is the average of Research Octane Number (RON) and Motor Octane Number (MON). Fuels with higher AKI are expected to have better knock mitigating properties, enabling the engine to run closer to Maximum Brake Torque (MBT) spark timing in the knock limited region. The work done in part I of the study related increased knock tolerance due to water injection to increased fuel AKI, thus establishing an ‘effective AKI’ due to water injection. This paper builds upon the work done in part I of the study by repeating a part of the test matrix with Primary Reference Fuels (PRFs), with iso-octane (PRF100) as the reference fuel and lower PRFs used to match its performance with the help of port water injection.

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route.

As the world searches for ways to reduce humanity’s impact on the environment, the automotive industry looks to extend the viable use of the gasoline engine by improving efficiency. One way to improve engine efficiency is through more effective control. Torque-based control is critical in modern cars and trucks for traction control, stability control, advanced driver assistance systems, and autonomous vehicle systems. Closed loop torque-based engine control systems require feedback signal(s); indicated mean effective pressure (IMEP) is a useful signal but is costly to measure directly with in-cylinder pressure sensors. Previous work has been done in torque and IMEP estimation using crankshaft acceleration and ion sensors, but these systems lack accuracy in some operating ranges and the ability to estimate cycle-cycle variation.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

Eco Approach and Departure (Eco-AnD) is a Connected Automated Vehicle (CAV) technology aiming to reduce energy consumption for crossing a signalized intersection or set of intersections in a corridor that features vehicle-to-infrastructure (V2I) communication capability. This research focuses on developing a Dynamic Programming (DP) based algorithm for a PHEV operating in Charge Depleting mode. The algorithm used the Reduced Order Energy Model (ROM) to capture the vehicle powertrain characteristics and road grade to capture the road dynamics. The simulation results are presented for a real-world intersection and 20-25% energy benefits are shown by comparing against a simulated human driver speed profile. The vehicle-level validation of the developed algorithm is carried out by performing closed-course track testing of the optimized speed solutions on a real CAV vehicle.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

As wireless devices and cellular networks continue to evolve, opportuvnities are created for enhancing the overall user experience with telematics related services. This paper discusses the pros and cons of por phone systems and embedded phone systems as conduits for telematics applications. Methods to enhance embedded in-vehicle telematics systems to include operation with handheld wireless devices on both Wide Area Networks (WAN) and Wireless Local Area Networks (WLAN) will also be presented. Services will be discussed that allow vehicles and wireless devices to interact with each other and with remote servers. Implementation options will be explored along with an analysis of the key players in the telematics supply chain (i.e., OEMs, Suppliers, Carriers, Call Centers, Consumers) who ultimately benefit from each approach.