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A Connected Controls and Optimization System for Vehicle Dynamics and Powertrain Operation on a Light-Duty Plug-In Multi-Mode Hybrid Electric Vehicle

Michigan Technological University-Joseph Oncken, Joshua Orlando, Pradeep K. Bhat, Brandon Narodzonek, Christopher Morgan, Darrell Robinette, Bo Chen, Jeffrey Naber
  • Technical Paper
  • 2020-01-0591
To be published on 2020-04-14 by SAE International in United States
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. Tools at the powertrain level include PHEV mode blending, predictive drive-unit state control, and non-linear model predictive control powertrain power split management. These tools were developed with the capability of being implemented in a real-time vehicle control system. As a result, many of the developed technologies have been demonstrated in real-time using a fleet of…
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PHEV Real World Driving Cycle Energy and Fuel and Consumption Reduction Potential for Connected and Automated Vehicles

Michigan Technological University-Darrell Robinette, Eric Kostreva, Alexandra Krisztian, Anthony Lackey, Christopher Morgan, Joshua Orlando, Neeraj Rama
Published 2019-04-02 by SAE International in United States
This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge. After completing 30 baseline drive cycles, a design for six sigma (DFSS) L18 array was designed to look at sensitivity of a range of parameters to energy consumption as related to connected and automated vehicles to target highest return on engineering development effort. The parameters explored in the DFSS array that showed the most sensitivity, in order of…
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Route-Optimized Energy Management of Connected and Automated Multi-Mode Plug-In Hybrid Electric Vehicle Using Dynamic Programming

Michigan Technological University-Neeraj Rama, Huanqing Wang, Joshua Orlando, Darrell Robinette, Bo Chen
Published 2019-04-02 by SAE International in United States
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. The objective of the optimizer is to enable future Connected and Automated Vehicles (CAVs) to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile information from Intelligent Transportation Systems (ITS), Internet of Things (IoT), High-definition Mapping, and onboard sensing technologies. Emphasis is placed on runtime minimization to quickly react and plan an optimal mode scheme in highly dynamic road conditions with minimal computational resources. On-road performance of the…
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Control Strategy and Energy Recovery Potential for P2 Parallel Hybrid Step Gear Automatic Transmissions

SAE International Journal of Advances and Current Practices in Mobility

Michigan Technological University-Darrell Robinette, Joshua Orlando
  • Journal Article
  • 2019-01-1302
Published 2019-04-02 by SAE International in United States
The purpose of this investigation is to present a control strategy and energy recovery potential for P2 parallel hybrid step gear automatic transmissions. The automatic transmission types considered for the investigation are rear wheel drive 8 speed dual clutch transmission and 8 speed planetary automatic equipped each equipped with an electric motor between the engine and transmission. The governing equations of clutch-to-clutch upshift controls are presented and are identical for each transmission type. Various strategies are explored for executing the upshift under a range of input torques, shift times and engine torque management approaches. The differences in energy recovery potential based upon control strategy is explored piecewise as well as through a DFSS study. On a comprehensive drive cycle consisting of FTP 75, US06 and HWFET test cycles, it is shown that upshift regen torque management can be equivalent to approximately 0.8% of the total fuel energy used. Additionally, it is shown that the utilization of the P2 electric motor is a further enabler to reduced shift times and improved shift quality at part throttle…
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