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Model-Based Approach to Estimate Fuel Savings from Series Hydraulic Hybrid Vehicle: Model Development and Validation
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 13, 2011 by SAE International in United States
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A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle. The system-level model of the hybrid vehicle is developed in a bottom-up fashion, developing the key component models first, which are then integrated according to the series hydraulic hybrid vehicle topology, to represent the system behavior. The parameter data is chosen to represent a Class 6 medium-duty parcel delivery truck.
The component models are validated using experimental data generated from in-house bench tests (for hydraulic pump/motors accumulator components) or provided by the manufacturer (for the diesel engine). An input-output validation technique was adopted with an upper spec limit of 10% on the error between output from the model output and experimental data. The system level model was validated by comparing experimental and simulated fuel economy for identical drive cycle inputs. The comparison was made for multiple vehicle payloads, with an average error of 7% for estimating fuel consumption for the series hydraulic hybrid vehicle. Further, to demonstrate the capability of the simulation framework, it is used to optimize the maximum system operating pressure for best fuel economy performance on a specified drive cycle.
CitationPatil, C., olson, M., Morris, B., Fortune, C. et al., "Model-Based Approach to Estimate Fuel Savings from Series Hydraulic Hybrid Vehicle: Model Development and Validation," SAE Technical Paper 2011-01-2274, 2011, https://doi.org/10.4271/2011-01-2274.
- Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles The National Academies Press 0-309-14983-5 250 2010
- Van Batavia, B. “Hydraulic Hybrid Vehicle Energy Management System,” SAE Technical Paper 2009-01-1772 2009 10.4271/2009-01-1772
- Eaton Hydraulic Launch Assist (HLA) System http://www.eaton.com/Eaton/ProductsServices/ProductsbyCategory/Truck/HybridPower/SystemsOverview/HydraulicHybrid/index.htm April 4 2011
- Lin, T. Wang, Q. Hu, B. Gong, W. Development of hybrid powered hydraulic construction machinery Automation in Construction 19 1 11 19 2010
- McKee, H. What Can NAC Do for Brown? Drive Military's Use of Hydraulic-Hybrid Technology TARDEC Quarterly October December 2008 24 25
- Wipke, K. Cuddy, M. Bharathan, D. Burch, S. Johnson, V. Markel, A. Sprik, S. Advisor 2.0: A Second-Generation Advanced Vehicle Simulator for Systems Analysis North American EV & Infrastructure Conference and Exposition (NAEVI 98) Phoenix, Arizona December 3 4 1998
- Rousseau, A. Pasquier, M. Validation of Hybrid Modeling Software (PSAT) Using Its Extension for Prototyping (PSAT-PRO) Global Powertrain Congress Detroit, MI June 5 7 2001
- Wu, B. Lin, C. Filipi, Z. Peng, H. Assanis, D. Optimal Power Management for a Hydraulic Hybrid Delivery Truck Vehicle System Dynamics 42 1-2 23 40 2004
- Kim, Y. Filipi, Z. “Simulation Study of a Series Hydraulic Hybrid Propulsion System for a Light Truck,” SAE Technical Paper 2007-01-4151 2007 10.4271/2007-01-4151
- Code of Federal Regulations, Title 40, Part 86, Appendix 1
- Optimization Toolbox User's Guide - Version 3.1.2 The Mathworks, Inc. Natick, MA, USA 2007