Developing FleetCalc to Reshape Our Nation's Vehicle Fleets

IMPACT. 1: FleetCalc will be the first online tool to provide accurate information on alternatives for Fleet vehicles based on real vehicle performance data and use patterns. Fleetcalc is a computer simulation that uses real vehicle data and sophisticated computer algorithms to provide fleet owners and policymakers with an ability to understand the impact of different technology options, fuel choices, driving styles, vehicle accessories and policy incentives on the cost and performance of various vehicles. Thus far, the team has:. Completed Comparison Assessment of other fleet calculators. Evaluated vehicle technologies and options to determine technical inputs to program. Surveyed and interviewed various stakeholders for needs and wants for program. Determined input and output structures. Developed initial economic analysis. Initiated Discussion on user interface prototype. Built initial web-based interface prototypes. Initiated initial fleet owner review. Developed preliminary framework for education.OSU PARTNERS: College of Engineering; Center for Automotive Research; John Glenn School of Public AffairsCOMMUNITY PARTNERS: Various vehicle fleet ownersPRIMARY CONTACT: Giorgio Rizzoni ([email protected]); Beth-Anne Schuelke-Leech ([email protected])Fleet owners now have a plethora of fuel options, vehicle types and technologies to choose from. There is a huge amount of information available on these options, some of which is contradictory, hard to compare, misleading or false. This same gauntlet is faced by policy makers who look to formulate strategies to accomplish a particular goal, or who wonder what the implications are of a particular program or initiative. Complex fleet calculators have been developed, giving fleet owners detailed information on the implications of a particular vehicle option. These fleet calculators require large amounts of data, and their results are complex and difficult to interpret

Developing FleetCalc to Reshape Our Nation's Vehicle Fleets

IMPACT. 1: FleetCalc will be the first online tool to provide accurate information on alternatives for fleet vehicles based on real vehicle performance data and use patterns. Fleetcalc is a computer simulation that uses real vehicle data and sophisticated computer algorithms to provide fleet owners and policymakers with an ability to understand the impact of different technology options, fuel choices, driving styles, vehicle accessories and policy incentives on the cost and performance of various vehicles. Thus far, the team has: Completed comparison assessment of other fleet calculators. Evaluated vehicle technologies and options to determine technical inputs to program. Surveyed and interviewed various stakeholders for needs and wants for program. Determined input and output structures. Developed initial economic analysis. Completed discussion on user interface prototype. Built initial web-based interface prototypes. Completed initial fleet owner review. Developed preliminary framework for education.OSU PARTNERS: College of Engineering; Center for Automotive Research; John Glenn School of Public AffairsCOMMUNITY PARTNERS: Various vehicle fleet ownersPRIMARY CONTACT: Giorgio Rizzoni ([email protected]); Beth-Anne Schuelke-Leech ([email protected])Fleet owners now have a plethora of fuel options, vehicle types and technologies to choose from. There is a huge amount of information available on these options, some of which is contradictory, hard to compare, misleading or false. This same gauntlet is faced by policy makers who look to formulate strategies to accomplish a particular goal, or who wonder what the implications are of a particular program or initiative. Complex fleet calculators have been developed, giving fleet owners detailed information on the implications of a particular vehicle option. These fleet calculators require large amounts of data, and their results are complex and difficult to interpret

Route Generation Methodology for Energy Efficiency Evaluation of Connected and Automated Vehicles

Evaluation of the energy savings potential of Connected and Automated Vehicles (CAVs) technologies necessitates a representative baseline that accounts for the inherent variability due to route, terrain, traffic, traffic lights, etc., in real-world driving conditions. While considerable work has been done in the field of optimal energy management, eco-driving and eco-routing of CAVs, few contributions have addressed the creation of a representative baseline to realistically evaluate the energy savings potential of these technologies. This work proposes a route generation methodology based on leveraging a high-dimension driving dataset to construct diverse subset of synthetic driving trips and synthetic routes for large scale evaluation of energy consumption of CAVs. The generated synthetic routes can then be used to extract real-world routes from open-source mapping platforms, which have similar characteristics as the generated synthetic routes

A novel mechanical analogy based battery model for SoC estimation using a multi-cell EKF

The future evolution of technological systems dedicated to improve energy efficiency will strongly depend on effective and reliable Energy Storage Systems, as key components for Smart Grids, microgrids and electric mobility. Besides possible improvements in chemical materials and cells design, the Battery Management System is the most important electronic device that improves the reliability of a battery pack. In fact, a precise State of Charge (SoC) estimation allows the energy flows controller to exploit better the full capacity of each cell. In this paper, we propose an alternative definition for the SoC, explaining the rationales by a mechanical analogy. We introduce a novel cell model, conceived as a series of three electric dipoles, together with a procedure for parameters estimation relying only on voltage measures and a given current profile. The three dipoles represent the quasi-stationary, the dynamics and the istantaneous components of voltage measures. An Extended Kalman Filer (EKF) is adopted as a nonlinear state estimator. Moreover, we propose a multi-cell EKF system based on a round-robin approach to allow the same processing block to keep track of many cells at the same time. Performance tests with a prototype battery pack composed by 18 A123 cells connected in series show encouraging results.Comment: 8 page, 12 figures, 1 tabl

A TECHNICAL REPORT ON A POLYTOPIC SYSTEM APPROACH FOR THE HYBRID CONTROL OF A DIESEL ENGINE USING VGT/EGR

This paper develops a hybrid/gain scheduled control to move a diesel engine through a driving profile represented as a set of 12 operating points in the 7-dimensional state space of a 7th order nonlinear state model. The calculations for the control design are based on a 3rd order(reduced) model of the Diesel engine on which state space is projected the 12 operating points. About each operating point, we generate a 3rd order nonlinear error models of the Diesel engine. Using the error model for each operating point, a control design is set forth as a system of LMI\u27s. The solution of each system of LMI\u27s produces a norm bounded controller guaranteeing that x x i d i d - Æ 1 where xi d is the i-th desired operating point in the 3-dimensional state space. The control performance is then evaluated on the 7th order model

Intelligent energy management in hybrid electric vehicles

The modelling and simulation approach is employed to develop an intelligent energy management system for hybrid electric vehicles. The aim is to optimize fuel consumption and reduce emissions. An analysis of the role of drivetrain, energy management control strategy and the associated impacts on the fuel consumption with combined wind/drag, slope, rolling, and accessories loads are included.<br /

Improving Computational Efficiency for Energy Management Systems in Plug-in Hybrid Electric Vehicles Using Dynamic Programming Based Controllers

Reducing computational time has become a critical issue in recent years, particularly in the transportation field, where the complexity of scenarios demands lightweight controllers to run large simulations and gather results to study different behaviors. This study proposes two novel formulations of the Optimal Control Problem (OCP) for the Energy Management System of a Plug-in Hybrid Electric Vehicle (PHEV) and compares their performance with a benchmark found in the literature. Dynamic Programming was chosen as the optimization algorithm to solve the OCP in a Matlab environment, using the DynaProg toolbox. The objective is to address the optimality of the fuel economy solution and computational time. In order to improve the computational efficiency of the algorithm, an existing formulation from the literature was modified, which originally utilized three control inputs. The approach involves leveraging the unique equations that describe the Input-Split Hybrid powertrain, resulting in a reduction of control inputs firstly to two and finally to one in the proposed solutions. The aforementioned formulations are referred to as 2-Controls and a 1-Control. Virtual tests were conducted to evaluate the performance of the two formulations. The simulations were carried out in various scenarios, including urban and highway driving, to ensure the versatility of the controllers. The results demonstrate that both proposed formulations achieve a reduction in computational time compared to the benchmark. The 2-Controls formulation achieved a reduction in computational time of approximately 40 times, while the 1-Control formulation achieved a remarkable reduction of approximately 850 times. These reductions in computational time were achieved while obtaining a maximum difference in fuel economy of approximately 1.5% for the 1-Control formulation with respect to the benchmark solution. Overall, this study provides valuable insights into the development of efficient and optimal controllers for PHEVs, which can be applied to various transportation scenarios. The proposed formulations reduce computational time without sacrificing the optimality of the fuel economy solution, making them a promising approach for future research in this area

On the representation of sensor faults in fault detection filters

This paper presents an extension of the well-known Beard-Jones detection filter that permits isolation of sensor faults in a dynamic system to a fixed direction in output space. The method is based on augmenting the system equations by an auxiliary state to represent the dynamic behavior of the sensor fault, and in effect converts the sensor fault into the same form as an actuator fault. The only condition required is observability of the original system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31239/1/0000145.pd

Sliding mode control of spatial mechanical systems decoupling translation and rotation

This paper looks at the robust trajectory control of spatial mechanical systems using sliding mode techniques. Two distinctions of the proposed method from reported methods are: (1) The measure of attitudinal error used is intrinsically defined, Euclidean-geometric, and intuitive. From Euler's theorem it follows that given a desired and actual attitude of a rigid body there exists an axis and angle of rotation relating the two attitudes. This defines a relative rotation vector, which is used as an intrinsically defined, intuitive measure of error. Reported methods use algebraic differences of entities such as generalized coordinates representing attitude. While functionally correlated to attitudinal error, these measures are not intrinsically defined. (2) A novel, dynamically nonlinear sliding function is used that results in a simple control law. The parameters of this function are dynamically and geometrically intuitive. Simulation results are given for a spacecraft tracking a complex desired trajectory

Dynamic modeling of a hybrid electric drivetrain for fuel economy, performance and driveability evaluations

ABSTRACT Both automakers and customers keep on pursuing better fuel economy, performance and driveability. A &quot;mild&quot; hybrid drivetrain is of great interest due to its potential capability on improving these targets. This drivetrain contains a spark ignition (SI) engine, an integrated starter/alternator (ISA), a torque converter (TC), a continuously variable transmission (CVT), a final drive (FD), a driveshaft, a brake-by-wire (BBW) system and wheels. While the challenge is to model and to develop an optimal control algorithm for this hybrid electric vehicle (HEV), this paper will focus only on the modeling aspect. Model-based control design and the nature of human perceptible driveability issues require low-frequency dynamic models. Therefore, a nonlinear control-oriented model which is sufficiently accurate but not excessively complicated is proposed here. Simulation results demonstrate that this model is effective to capture the main behaviors of vehicle dynamics and to evaluate fuel economy, performance and driveability objectively. NOMENCLATUR