Analyzing Drive Cycles for Hybrid Electric Vehicle Simulation and Optimization

2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Benjamin M. Geller ◽  
Thomas H. Bradley
Keyword(s):  
Hybrid Electric Vehicle ◽  
Energy Use ◽  
Computational Cost ◽  
Vehicle Design ◽  
Optimized Design ◽  
Drive Cycle ◽  
Vehicle Performance ◽  
Design And Optimization ◽  
Simulation And Optimization ◽  
Vehicle Simulation

System design tools including simulation and component optimization are an increasingly important component of the vehicle design process, placing more emphasis on early stages of design to reduce redesign and enable more robust design. This study focuses on the energy use and power management simulations used in vehicle design and optimization. Vehicle performance is most often evaluated in simulation, physical testing, and certification using drive cycle cases (also known as dynamometer schedules or drive schedules). In vehicle optimization studies, the information included in each drive cycle has been shown to influence the attributes of the optimized vehicle, and including more drive cycles in simulation optimizations has been shown to improve the robustness of the optimized design. This paper aims to quantitatively understand the effect of drive cycles on optimization in vehicle design and to specify drive cycles that can lead to robust vehicle design with minimal simulation. Two investigations are performed in service of this objective; investigation 1 tests how different combinations of drive cycles affect optimized vehicle performance and design variables (DV); investigation 2 evaluates the use of stochastic drive cycles for improving the robustness of vehicle designs without adding computational cost to the design and optimization process.

Battery Sizing as a Function of Powertrain Component Efficiencies for Various Drive Cycles

2011 ◽  
Author(s):  
Lynn R. Gantt ◽  
R. Jesse Alley ◽  
Douglas J. Nelson
Keyword(s):  
Real World ◽  
Hybrid Electric Vehicle ◽  
Energy Use ◽  
Net Energy ◽  
Vehicle Speed ◽  
Drive Cycle ◽  
Component Efficiency ◽  
Technical Specifications ◽  
Hybrid Electric ◽  
The Individual

The market segment of hybrid-electric and full function electric vehicles is growing within the automotive transportation sector. While many papers exist concerning fuel economy or fuel consumption and the limitations of conventional powertrains, little published work is available for vehicles which use grid electricity as an energy source for propulsion. Generally, the emphasis is put solely on the average drive cycle efficiency for the vehicle with very little thought given to propelling and braking powertrain losses for individual components. The modeling section of this paper will take basic energy loss equations for vehicle speed and acceleration, along with component efficiency information to predict the grid energy consumption in AC Wh/km for a given drive cycle. An electric-only range target is established as part of the vehicle technical specifications. This set range along with component characteristics will impact the sizing of the energy storage subsystem. To demonstrate the usefulness in understanding powertrain losses, the energy use is described in propelling, braking, idle, and charging cases. A simulation focusing on battery sizing to meet power and range requirements shows the impacts of friction brakes, regenerative braking fraction, and average motor efficiency. Vehicle characteristics such as, but not limited to, a range extender application, electric-only vehicle range, and acceleration performance are explained as well. The model is correlated to real world vehicle data for a custom-built plug-in hybrid electric vehicle. By using the Virginia Tech Range Extended Crossover (VTREX) and collecting data from testing, the parameters that the model is based on will be correlated with real world test data. The paper presents a propelling, braking, and net energy weighted drive cycle averaged efficiency that can be used to calculate the losses for a given cycle. In understanding the losses at each component, not just the individual efficiency, areas for future vehicle improvement can be identified to reduce petroleum energy use and greenhouse gases.

scholarly journals Plug-In Hybrid Vehicle Simulation: How Battery Weight and Charging Patterns Impact Cost, Fuel Consumption, and CO2 Emissions

2008 ◽  
Author(s):  
Richard Hauffe ◽  
Constantine Samaras ◽  
Jeremy J. Michalek
Keyword(s):  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Ghg Emissions ◽  
Simulation Models ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Transportation Sector ◽  
Battery Capacity ◽  
Impact Cost ◽  
Small Capacity

Plug-in hybrid electric vehicle (PHEV) technology is receiving attention as an approach to reducing U.S. dependency on foreign oil and emissions of greenhouse gases (GHG) from the transportation sector. Because plug-in vehicles require large batteries for energy storage, battery weight can have a significant impact on vehicle performance: Additional storage capacity increases the range that a PHEV can travel on electricity from the grid; however, the associated increased weight causes reduced efficiency in transforming electricity and gasoline into miles driven. We examine vehicle simulation models for PHEVs and identify trends in fuel consumption, operating costs, and GHG emissions as battery capacity is increased. We find that PHEVs with large battery capacity consume less gasoline than small capacity PHEVs when charged every 200 miles or less. When charged frequently, small capacity PHEVs are less expensive to operate and release fewer GHGs, but medium and large capacity PHEVs are more efficient for drivers that charge every 25–100 miles. While statistics on average commute length suggest that frequent charges are possible, answering the question of which PHEV designs will best help to achieve national goals will require a realistic understanding of likely consumer driving and charging behavior as well as future trends in electricity generation.

Motor Parameters Matching Based on Motor Loss Model and the Actual Drive Cycle of Hybrid Electric Vehicle

2012 ◽  
Vol 246-247 ◽  
pp. 154-158
Author(s):  
Jing Wen ◽  
Liang Chu ◽  
Jun Nian Wang ◽  
Jian Kun Yin ◽  
Yan Bo Wang
Keyword(s):  
Hybrid Electric Vehicle ◽  
Power Performance ◽  
Test Cycle ◽  
Drive Cycle ◽  
Statistical Tool ◽  
Traction Motor ◽  
Loss Model ◽  
Vehicle Simulation ◽  
Motor Test ◽  
Continuous Parameter

The paper describes a way of matching the traction motor’s continuous parameters without changing the vehicle’s power performance. First, the traction motor’s peak parameters were matched according to the power performance of the HEV. Second, using the statistical tool, the region of the continuous parameter is set according to traction motor working distribution under actual drive cycle. Third, the continuous parameters were matched according to the motor loss model and the motor test cycle. Finally, vehicle simulation is done in CRUISE, simulation results show HEV traction motor matched using this method can improve the economy performance of the vehicle under certain drive cycle.

SUAVE: An Open-Source Environment for Conceptual Vehicle Design and Optimization

2016 ◽  
Author(s):  
Emilio M. Botero ◽  
Andrew Wendorff ◽  
Timothy MacDonald ◽  
Anil Variyar ◽  
Julius M. Vegh ◽  
...  
Keyword(s):  
Open Source ◽  
Vehicle Design ◽  
Design And Optimization

scholarly journals Design and Optimization of a Centrifugal Pump for Slurry Transport Using the Response Surface Method

Machines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 60
Author(s):  
Khaled Alawadhi ◽  
Bashar Alzuwayer ◽  
Tareq Ali Mohammad ◽  
Mohammad H. Buhemdi
Keyword(s):  
Response Surface ◽  
Centrifugal Pump ◽  
Industrial Applications ◽  
Pump Efficiency ◽  
Optimized Design ◽  
Centrifugal Pumps ◽  
Local Pressure ◽  
Design And Optimization ◽  
Geometry Characteristic ◽  
Line Design

Since centrifugal pumps consume a mammoth amount of energy in various industrial applications, their design and optimization are highly relevant to saving maximum energy and increasing the system’s efficiency. In the current investigation, a centrifugal pump has been designed and optimized. The study has been carried out for the specific application of transportation of slurry at a flow rate of 120 m3/hr to a head of 20 m. For the optimization process, a multi-objective genetic algorithm (MOGA) and response surface methodology (RSM) have been employed. The process is based on the mean line design of the pump. It utilizes six geometric parameters as design variables, i.e., number of vanes, inlet beta shroud, exit beta shroud, hub inlet blade draft, Rake angle, and the impeller’s rotational speed. The objective functions employed are pump power, hydraulic efficiency, volumetric efficiency, and pump efficiency. In this reference, five different software packages, i.e., ANSYS Vista, ANSYS DesignModeler, response surface optimization software, and ANSYS CFX, were coupled to achieve the optimized design of the pump geometry. Characteristic maps were generated using simulations conducted for 45 points. Additionally, erosion rate was predicted using 3-D numerical simulations under various conditions. Finally, the transient behavior of the pump, being the highlight of the study, was evaluated. Results suggest that the maximum fluctuation in the local pressure and stresses on the cases correspond to a phase angle of 0°–30° of the casing that in turn corresponds to the maximum erosion rates in the region.

Analysis and Control of Torque Split in Hybrid Electric Vehicles by Incorporating Powertrain Dynamics

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Mehran Bidarvatan ◽  
Mahdi Shahbakhti
Keyword(s):  
Steady State ◽  
Energy Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Internal Combustion Engines ◽  
Dynamic Models ◽  
Management Control ◽  
Drive Cycle ◽  
Hybrid Electric

Hybrid electric vehicle (HEV) energy management strategies usually ignore the effects from dynamics of internal combustion engines (ICEs). They usually rely on steady-state maps to determine the required ICE torque and energy conversion efficiency. It is important to investigate how ignoring these dynamics influences energy consumption in HEVs. This shortcoming is addressed in this paper by studying effects of engine and clutch dynamics on a parallel HEV control strategy for torque split. To this end, a detailed HEV model including clutch and ICE dynamic models is utilized in this study. Transient and steady-state experiments are used to verify the fidelity of the dynamic ICE model. The HEV model is used as a testbed to implement the torque split control strategy. Based on the simulation results, the ICE and clutch dynamics in the HEV can degrade the control strategy performance during the vehicle transient periods of operation by around 8% in urban dynamometer driving schedule (UDDS) drive cycle. Conventional torque split control strategies in HEVs often overlook this fuel penalty. A new model predictive torque split control strategy is designed that incorporates effects of the studied powertrain dynamics. Results show that the new energy management control strategy can improve the HEV total energy consumption by more than 4% for UDDS drive cycle.

Development of a Driving Simulator for Virtual Evaluation of Vehicle Dynamics

2010 ◽  
Author(s):  
A. M. Sharaf
Keyword(s):  
Performance Evaluation ◽  
Vehicle Dynamics ◽  
Driving Simulator ◽  
Field Testing ◽  
Vehicle Performance ◽  
Vehicle Simulation ◽  
Virtual Platform ◽  
The Cost ◽  
Vehicle Testing ◽  
Simulation Package

This paper delineates the conceptual algorithms of a driving simulator which is intended for vehicle performance evaluation and to act as a virtual platform for research studies and therefore eliminates the cost and dangerous of field testing. A virtual proving ground for vehicle testing has been devised through which virtual handling, traction and ride tests can be performed. A fully instrumented simulator cabin combining the driver and the vehicle simulation package is developed. Different vehicle configurations are simulated during typical sever manoeuvres which reflects the robustness and fidelity of the devised simulator.

scholarly journals Development of a Hybrid Electric Vehicle Simulation Tool with a Rule-Based Topology

2021 ◽  
Vol 11 (23) ◽  
pp. 11319
Author(s):  
Hyun Woo Won
Keyword(s):  
Hybrid Electric Vehicle ◽  
Hybrid Simulation ◽  
Rule Base ◽  
Simulation Tool ◽  
Control Logic ◽  
Rule Based ◽  
Vehicle Simulation ◽  
Wide Range ◽  
Hybrid Electric ◽  
And Control

The performance of hybrid electric vehicles (HEVs) greatly depends on the various sub-system components and their architecture, and designers need comprehensive reviews of HEVs before vehicle investigation and manufacturing. Simulations facilitate development of virtual prototypes that make it possible to rapidly see the effects of design modifications, avoiding the need to manufacture multiple expensive physical prototypes. To achieve the required levels of emissions and hardware costs, designers must use control strategies and tools such as computational modeling and optimization. However, most hybrid simulation tools do not share their principles and control logic algorithms in the open literature. With this motivation, the author developed a hybrid simulation tool with a rule-based topology. The major advantage of this tool is enhanced flexibility to choose different control and energy management strategies, enabling the user to explore a wide range of hybrid topologies. The tool provides the user with the ability to modify any sub-system according to one’s own requirements. In addition, the author introduces a simple logic control for a rule-base strategy as an example to show the flexibility of the tool in allowing the adaptation of any logic algorithm by the user. The results match the experimental data quite well. Details regarding modeling principle and control logic are provided for the user’s benefit.

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