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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

A growing number of electric vehicles (EV) and hybrid electric vehicles (HEV) in the present market depicts the rapid growing demand for energy storage systems. The battery’s main peculiarities must be the power density and reliability over time. The temperature strongly affects battery performance for low and high intensity. In particular, the management of the heat generated by the battery itself is one of the main aspects to handle to preserve the performance over time. The objective of this paper is to compare the surface temperature of the lithium-ion polymer battery at different discharging rates by infrared thermography. Thermal imaging is performed to detect the battery surface temperature distribution, focusing on its variation over time and the local inhomogeneity. Temperature measurements are then used to estimate the contributions of the different heat transfer mechanisms for the dissipation of the heat generated by the battery.

New internal combustion engines (ICE) are characterized by increasing maximum efficiency, thanks to the adoption of strategies like Atkinson cycle, downsizing, cylinder deactivation, waste heat recovery and so on. However, the best performance is confined to a limited portion of the engine map. Moreover, electric driving in urban areas is an increasingly pressing request, but battery electric vehicles use cannot be easily spread, due to limited vehicle autonomy and recharging issues. Therefore, hybrid propulsion systems are under development, in order to reduce vehicle fuel consumption, by decoupling the ICE running from road load, as well as to permit energy recovery and electric driving. This paper analyses a new-patented solution for power split hybrid propulsion system with gearbox. The system comprises an auxiliary power unit, adapted to store and/or release energy, and a planetary gear set, which is interposed between the ICE and the gearbox.

In this paper, the results of an extensive experimental analysis regarding a twin-cylinder spark-ignition turbocharged engine are employed to build up an advanced 1D model, which includes the effects of cycle-by-cycle variations (CCVs) on the combustion process. Objective of the activity is to numerically estimate the CCV impact primarily on fuel consumption and knock behavior. To this aim, the engine is experimentally characterized in terms of average performance parameters and CCVs at high and low load operation. In particular, both a spark advance and an air-to-fuel ratio (α) sweep are actuated. Acquired pressure signals are processed to estimate the rate of heat release and the main combustion events. Moreover, the Coefficient of Variation of IMEP (CoVIMEP) and of in-cylinder peak pressure (CoVpmax) are evaluated to quantify the cyclic dispersion and identify its dependency on peak pressure position.

The technique of liquid Water Injection (WI) at the intake port of downsized boosted SI engines is a promising solution to improve the knock resistance at high loads. In this work, an existing 1D engine model has been extended to improve its ability to simulate the effects of the water injection on the flame propagation speed and knock onset. The new features of the 1D model include an improved treatment of the heat subtracted by the water evaporation, a newly developed correlation for the laminar flame speed, explicitly considering the amount of water in the unburned mixture, and a more detailed kinetic mechanism to predict the auto-ignition characteristics of fuel/air/water mixture. The extended 1D model is validated against experimental data collected at different engine speeds and loads, including knock-limited operation, for a twin-cylinder turbocharged SI engine.

Knock occurrence and fuel enrichment, which is required at high engine speed and load to limit the turbine inlet temperature, are the major obstacles to further increase performance and efficiency of down-sized turbocharged spark ignited engines. A technique that has the potential to overcome these restrictions is based on the injection of a precise amount of water within the mixture charge that can allow to achieve important benefits on knock mitigation, engine efficiency, gaseous and noise emissions. One of the main objectives of this investigation is to demonstrate that water injection (WI) could be a reliable solution to advance the spark timing and make the engine run at leaner mixture ratios with strong benefits on knock tendency and important improvement on fuel efficiency.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

The detailed study of part-load conditions is essential to characterize engine-out emissions in key operating conditions. The relevance of part-load operations is further emphasized by the recent regulations such as the new WLTP standard. Combustion development at part-load operations depends on a complex interplay between moderate turbulence levels (low engine speed and tumble ratio), low in-cylinder pressure and temperature, and stoichiometric-to-lean mixture quality (to maximize fuel efficiency). From a modelling standpoint, the reduced turbulence intensity compared to full-load operations complicates the interaction between different sub-models (e.g., reconsideration of the flamelet hypothesis adopted by common combustion models). In this article, the authors focus on chemistry-based simulations for laminar flame speed of gasoline surrogates at conditions typical of part-load operations. The analysis is an extension of a previous study focused on full-load operations.

In this paper the characteristics of a mixture of glycerol-based ethers usable in a compression ignition engine are investigated, in terms of efficiency and emissions. Alternative pathways for the energetic exploitation of biodiesel derived glycerol became of increasing interest as the biodiesel production was increased worldwide. Because of its detrimental physical and chemical properties, raw glycerol is hardly usable in conventional internal combustion engines (ICE). However, etherification of glycerol with tert-butyl alcohol and isobutylene allows obtaining a mixture mainly composed of higher glycerol ethers (GEM) suitable for compression ignition engines. Thus, the aim of this research study was to test a mixture of mono-, di- and tri-tert-butyl ethers of glycerol in blend with a commercial diesel fuel in a compression ignition engine, evaluating the fuel efficiency and the impact on the pollutant emissions.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

Idle Speed Control plays a crucial role to reduce fuel consumption that turns in both a direct economic benefit for customers and CO\d reduction particularly important to tackle the progressive global environmental warming. Typically, control strategies available in the automotive literature solve the idle speed control problem acting both on the throttle position and the spark advance, while the Air-Fuel Ratio (AFR), that strongly affects the indicated engine torque, is kept at the stoichiometric value for the sake of emission reduction. Gasoline Direct Injection (GDI) engines, working lean and equipped with proper mechanisms to reduce NOx emissions, overcome this limitation allowing the AFR to be used for the idle speed regulation.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

In this paper, the conversion of a production sport utility vehicle (SUV) to a hybrid electric vehicle utilizing a through-the-road parallel hybrid configuration is presented. The uniqueness of this design comes from its ability to decouple the front and rear drivetrain to simplify the packaging of underbody components. The Hybrid Theory utilizes a 2.0L, 4-cylinder engine that supplies 101kW (135hp) to the front wheels and a DC motor that supplies an additional 53kW (70hp) to the rear wheels to achieve the competition goals of a 25% improvement in fuel economy, a reduction in Green House Gas (GHG) emissions, as well as maintaining stock performance. The effects on drivability, manufacturing, fuel economy, emissions, and performance are presented along with the design, selection, and implementation of all of the vehicle conversion components.

Internal combustion engines for vehicle propulsion are more and more sophisticated due to increasingly restrictive environmental regulations. In case of heavy-duty engines, Compressed Natural Gas (CNG) fueling coupled with Three-Way Catalyst (TWC) and Exhaust Gas Recirculation (EGR) can help in meeting the imposed emission limits and preventing from thermal stress of engine components. To cope with the new issues associated with the more complex hardware and to improve powertrain performance and reliability and after-treatment efficiency, the engine control strategies must be reformulated. The paper focuses on the steady-state optimization of control parameters for a heavy-duty engine fueled by CNG and equipped with turbocharger and EGR. The optimization analysis is carried out to design EGR, spark timing and wastegate control, aimed at increasing fuel economy while reducing in-cylinder temperature to prevent from thermal stress of engine components.

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.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.

GDI injection systems have become dominant in passenger cars due to their flexibility in managing and advantages in the fuel economy. With the increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the fuel spray behavior has become essential. Different engine loads produce in a variety of fuel supplying conditions that affect the air/fuel mixture preparation and influence the efficiency and pollutant production. The flash boiling is a particular state that occurs for peculiar thermodynamic conditions of the engine. It could strongly influence the mixture in sub-atmospheric environments with detrimental effects on emissions. In order to obtain an in-depth understanding of the flash boiling phenomena, it is necessary to study the parameters influencing the mixture formation and their appearance in diverse engine conditions.

This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller.

Considering the generalized diversification of the energy mix, the use of alcohols as gasoline replacement is proposed as a viable option. Also, alternative control strategies for spark ignition engines (SI) such as lean operation and exhaust gas recirculation (EGR) are used on an ever wider scale for improving fuel economy and reducing the environmental impact of automotive engines. In order to increase the stability of these operating points, alternative ignition systems are currently investigated. Within this context, the present work deals about the use of plasma assisted ignition (PAI) in a direct injection (DI) SI engine under lean conditions and cooled EGR, with gasoline and n-butanol fueling. The PAI system was tested in an optically accessible single-cylinder DISI engine equipped with the head of a commercial turbocharged power unit with similar geometrical specifications (bore, stroke, compression ratio).