Neeraj Shidore

Automated Model Based Design Process to Evaluate Advanced Component Technologies

To reduce development time and introduce technologies faster to the market, many companies have been turning more and more to Model Based Design. In Model Based Design, the development process centers around a system model, from requirements capture and design to implementation and test. Engineers can skip over a generation of system design processes on the basis of hand coding and use graphical models to design, analyze, and implement the software that determines machine performance and behavior. This paper describes the process implemented in Autonomie, a Plug-and-Play Software Environment, to design and evaluate component hardware in an emulated environment. We will discuss best practices and provide an example through evaluation of advanced high-energy battery pack within an emulated Plug-in Hybrid Electric Vehicle.

Evaluation of cold temperature performance of the JCS-VL41M PHEV battery using Battery HIL

Plug-in hybrid electric vehicles (PHEVs) have been identified as an effective technology to displace petroleum by drawing significant off- board energy from the electrical grid. A plug-in vehicle uses a large capacity battery to operate in an electric-only or a blended mode of operation over a large SOC window (60-80% of total operational SOC) for maximum petroleum displacement. Some advanced chemistry batteries have show that low ambient (battery) temperature has a significant impact on the performance of a PHEV battery. This paper quantifies the impact of low ambient (battery) temperature on a PHEV electric range using Hardwarein-the-Loop (HIL) methods. Combining ultra capacitors with batteries could provide a solution to overcome PHEV battery performance limitations at low temperatures.

Trade-off between PHEV fuel efficiency and estimated battery cycle life with cost analysis

The battery life and cost of plug-in hybrid electric vehicles (PHEVs) are two key factors that impede the introduction of PHEVs in the current market. For a given drive pattern, battery cycle life has an inverse relationship with battery utilization, and gasoline savings (petroleum displacement) has a direct correlation with battery utilization. This paper attempts to determine the trade-off between battery cycle life and gasoline fuel savings by varying the battery utilization for a fixed distance and drive pattern. By varying the vehicle energy management, different battery utilization scenarios are created. Battery hardware-in-the-loop (a real battery tested in a virtual vehicle) is used to evaluate battery utilization under different vehicle energy management scenarios. The virtual vehicle is a real-time simulation of a power-split midsize vehicle, developed by using Argonnes Powertrain Simulation Analysis Toolkit (PSAT). The real battery is the JCS VL41M 10-kWH lithium-ion PHEV battery. Cost analysis provides insights into the economic impact of the above trade-off.

Component And Subsystem Evaluation In A Systems Context Using Hardware In The Loop

Hardware in the loop (HIL)/rapid control prototyping (RCP) is generally acknowledged to be a cost- and time-effective approach to test controllers/components/subsystems in a system context. Argonne National Laboratory has been using HIL to evaluate the potential of a plug-in hybrid battery in a vehicle (battery HIL). Argonne has also constructed a vehicle platform on wheels to evaluate different power train components on a chassis dynamometer - the mobile advanced technology testbed (MATT). This paper describes these two HIL projects and gives some preliminary results on all electric range (AER) tests conducted on both HIL platforms. These results are compared to simulation results obtained from Argonnes power train system analysis toolkit (PSAT).

Interdependence of System Control and Component Sizing for a Hydrogen-fueled Hybrid Vehicle

Argonne National Laboratory (ANL) researchers have embarked on an ambitious program to quantitatively demonstrate the potential of hydrogen as a fuel for internal combustion engines (ICEs) in hybrid-electric vehicle applications. In this initiative, ANL researchers need to investigate different hybrid configurations, different levels of hybridization, and different control strategies to evaluate their impacts on the potential of hydrogen ICEs in a hybrid system. Because of limitations in the choice of motor and battery hardware, a common practice is to fix the size of the battery and motor, depending on the hybrid configuration (starter/alternator, mild hybrid, or full hybrid) and to tune the system control for the above-available electrical power/ energy. ANL has developed a unique, flexible, Hardware-In-the-Loop (HIL) platform for advanced powertrain technology evaluation: The Mobile Advanced Technology Testbed (MATT). MATT has the flexibility to easily test advanced components in various hybrid configurations. In addition, MATT has the capability of emulating any size of motor and battery. Therefore, the powertrain under test can be evaluated with different levels of hybridization. The versatile control system software developed by ANL provides rapid evaluation of control options associated with each hybrid configuration and each level of hybridization. The powertrain currently under investigation at ANL consists of a supercharged hydrogen-fueled internal combustion engine and a dual clutch transmission. The engine and transmission are not emulated and are therefore fixed in terms of sizing. Since the motor and the battery are emulated, MATT makes it possible to resize the battery and the motor for every change in control strategy, thus enabling an iterative loop between control strategy and component sizing. This iterative sizing process would then result in components optimized for a control strategy. The ultimate aim of this iterative process is to identify the optimal control strategy and component sizing for a particular specifications set (performance and fuel economy). As a first step, this interdependent sizing process was studied in simulation only by using ANL-developed PSAT (Power-train System Analysis Toolkit) [1], and the results are presented in this paper. The next stage is to validate the simulation results with the test data collected on MATT for different levels of hybridization and different control strategies.

Electric Drive Vehicle Development and Evaluation Using System Simulation

Abstract To reduce development time and introduce technologies faster to the market, many companies have been moving to Model-based System Engineering (MBSE). In MBSE, the development process centers around a multi-physics model of the complete system being developed, from requirements to design, implementation and test. Engineers can avoid a generation of system design processes based on hand coding, and use graphical models to design, analyze, and implement the software that determines system performance and behavior. This paper describes the process implemented in Autonomie, a Plug-and-Play Software Environment, to design and evaluate electric drive powertrain and component technologies in a multi-physics environment. We will discuss best practices and provide examples of the different steps of the V-diagram including model-in-the-loop, software-in-the-loop and component-in-the-loop simulation.

Fuel Displacement Potential of a Thermoelectric Generator in a Conventional Vehicle

This paper evaluates the fuel displacement potential of a Thermoelectric Generator (TEG) device in a conventional gasoline vehicle using vehicle simulation and engine in the loop. A TEG device was modelled in Simulink, to exhibit the thermal and electrical characteristics of such a device. This TEG model was integrated into the vehicle simulation software, Autonomie and evaluated in a real engine - virtual vehicle scenario using Engine in the loop (EIL) technique. The EIL approach was used to evaluate the fuel consumption benefit of TEG under cold and hot conditions. The complete vehicle model was then validated and used to evaluate the impact of the current TEG system on additional drive cycles as well as future TEG systems (i.e. no device temperature limits). EIL evaluation shows a fuel economy gain within the current device of 1% on the US06 cycle. The simulation study will quantify the impact of driving cycles and TEG design on fuel displacement potential.

PHEV Energy Management Strategies at cold temperatures with Battery temperature rise and Engine efficiency Improvement considerations

Limited battery power and poor engine efficiency at cold temperature results in low plug in hybrid vehicle (PHEV) fuel economy and high emissions. Quick rise of battery temperature is not only important to mitigate lithium plating and thus preserve battery life, but also to increase the battery power limits so as to fully achieve fuel economy savings expected from a PHEV. Likewise, it is also important to raise the engine temperature so as to improve engine efficiency (therefore vehicle fuel economy) and to reduce emissions. One method of increasing the temperature of either component is to maximize their usage at cold temperatures thus increasing cumulative heat generating losses. Since both components supply energy to meet road load demand, maximizing the usage of one component would necessarily mean low usage and slow temperature rise of the other component. Thus, a natural trade-off exists between battery and engine warm-up. This paper compares energy management strategies for a power-split PHEV for their ability to warm –up the battery and the engine, and ultimately the resulting fuel economy. The engine model predicts engine fuel rate as a function of engine utilization history and starting temperature, apart from speed and torque. The battery temperature rise model is a function of battery utilization. Engine and battery utilization is varied by changing the control parameter - wheel power demand at which the engine turns ON. The paper analyses the sensitivity of fuel and electrical energy consumption to engine and battery temperature rise, for different driving distances and driver aggressivenes

Evaluation of Ethanol Blends for Plug-In Hybrid Vehicles Using Engine in the Loop

Their easy availability, lower well-to-wheel emissions, and relative ease of use with existing engine technologies have made ethanol and ethanol-gasoline blends a viable alternative to gasoline for use in spark-ignition (SI) engines. The lower energy density of ethanol and ethanol-gasoline blends, however, results in higher volumetric fuel consumption compared with gasoline. Also, the higher latent heat of vaporization can result in cold-start issues with higher-level ethanol blends. On the other hand, a higher octane number, which indicates resistance to knock and potentially enables more optimal combustion phasing, results in better engine efficiency, especially at higher loads. This paper compares the fuel consumption and emissions of two ethanol blends (E50 and E85) with those for gasoline when used in conventional (non-hybrid) and power-split-type plug-in hybrid electric vehicles (PHEVs). Engine-in-the-loop (EIL) test results from a previous study of an E85-series PHEV show about 4% lower fuel energy consumption than gasoline because of better engine efficiency at high loads. In a conventional vehicle, the decrease in fuel energy consumption when gasoline is compared with E85 is less than 1%. The series PHEV operates as an electric vehicle when in charge-depleting (CD) mode. For the power-split PHEV, the CD mode of operation has multiple, but infrequent, “engine on” events, resulting in different engine utilization than the series PHEV. Differences in the hybridization configuration also result in different regions of operation for the engine in the CD, as well as the charge-sustaining (CS), mode of operation. The vehicle control strategy for a particular configuration remains the same for the different fuel blends. For the power-split PHEV, we assess the sensitivity of fuel consumption and emissions to the three fuels using EIL testing and compare them with EIL results for a series PHEV and a conventional vehicle. We propose changes to the PHEV control strategy to optimize the vehicle system for each fuel blend and configuration.

Evaluation of ethanol blends for PHEVs using engine-in-the-loop

The easy availability, lower well-to-wheel emissions, and relative ease of use associated with existing engine technology have made ethanol and ethanol-gasoline blends a viable alternative to gasoline for spark-ignition (SI) engines. The lower energy density of ethanol and ethanol — gasoline blends results in higher volumetric fuel consumption than that associated with gasoline. On one hand, when higher-level ethanol blends are used, the higher latent heat of vaporization can result in cold-start issues. On the other hand, a higher octane number, which indicates resistance to knock and enables optimal combustion phasing, improves engine efficiency, especially at higher loads. This paper compares fuel consumption and emissions for two ethanol blends with gasoline (E50 and E85) for conventional (nonhybrid), and series-type plug-in hybrid vehicles. Each vehicle configuration results in different engine operating regimes and multiple engine ON events. For each vehicle type, the sensitivities of fuel consumption and emissions to the three fuels are assessed. The impacts of ethanol blends on fuel consumption and emissions depend on the engine operating regime. The combined impact on fuel economy that results from low energy density (negative impact) and higher efficiency at high engine loads (positive impact) is assessed for the series PHEV. Changes to the vehicle energy management strategy for the series PHEV are proposed based on the differences in fuel consumption for the different blends. In this study, Argonnes vehicle system simulation and control software AUTONOMIE was used to simulate the engine-in-the-loop process. This paper describes the process in the AUTONOMIE environment.