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 Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1140 ◽  
Author(s):  
H. Christopher Frey ◽  
Xiaohui Zheng ◽  
Jiangchuan Hu
Keyword(s):  
Real World ◽  
Hybrid Electric Vehicle ◽  
Energy Use ◽  
Average Energy ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Wide Range ◽  
Hybrid Electric ◽  
Cold Starts

Compared to comparably sized conventional light duty gasoline vehicles (CLDGVs), plug-in hybrid electric vehicles (PHEVs) may offer benefits of improved energy economy, reduced emissions, and the flexibility to use electricity as an energy source. PHEVs operate in either charge depleting (CD) or charge sustaining (CS) mode; the engine has the ability to turn on and off; and the engine can have multiple cold starts. A method is demonstrated for quantifying the real-world activity, energy use, and emissions of PHEVs, taking into account these operational characteristics and differences in electricity generation resource mix. A 2013 Toyota Prius plug-in was measured using a portable emission measurement system. Vehicle specific power (VSP) based modal average energy use and emission rates are inferred to assess trends in energy use and emissions with respect to engine load and for comparisons of engine on versus engine off, and cold start versus hot stabilized running. The results show that, compared to CLDGVs, the PHEV operating in CD mode has improved energy efficiency and lower CO2, CO, HC, NOx, and PM2.5 emission rates for a wide range of power generation fuel mixes. However, PHEV energy use and emission rates are highly variable, with periods of relatively high on-road emission rates related to cold starts.

scholarly journals Control Analysis of a Real-World P2 Hybrid Electric Vehicle Based on Test Data

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4092
Author(s):  
Woong Lee ◽  
Tacksu Kim ◽  
Jongryeol Jeong ◽  
Jaewoo Chung ◽  
Deokjin Kim ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Test Data ◽  
Real World ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuel Efficiency ◽  
Control Analysis ◽  
Vehicle Speed ◽  
Control Concept ◽  
Hybrid Electric

The control strategy of a hybrid electric vehicle (HEV) is generally not disclosed to public because it is a significant factor in determining the performance of the system. However, engineers desiring to understand the control concept of real-world HEVs can gain knowledge in various ways. In this study, we used test data obtained from a bench dynamometer and real driving to analyze the supervisory control strategy of Hyundai Ioniq Hybrid. This research can be described in three steps. First, an understanding of the mode control strategy is obtained by investigating the engine on/off behavior, which determines when the pure electric driving mode is used. Second, the shifting patterns are studied by observing the speed ratios according to the vehicle speed and the torque demand. Third, the strategy for distributing the torque between the engine and the motor is analyzed by studying the motor assistant operation. Based on the analyzed control concept, it is possible to understand the technical strategy for improving the fuel efficiency of the parallel hybrid system. This study would be useful for engineers who want to design controllers for HEVs, in that it provides the analyzed control concept and the real-world operating behaviors.

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.

Dynamic Programming-Informed Equivalent Cost Minimization Control Strategies for Hybrid-Electric Vehicles

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Dekun Pei ◽  
Michael J. Leamy
Keyword(s):  
Dynamic Programming ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Cost Minimization ◽  
Global Optimum ◽  
Robust Controller ◽  
Drive Cycle ◽  
Suggested Approach ◽  
Equivalence Factor ◽  
Hybrid Electric

This paper presents a direct mathematical approach for determining the state of charge (SOC)-dependent equivalent cost factor in hybrid-electric vehicle (HEV) supervisory control problems using globally optimal dynamic programming (DP). It therefore provides a rational basis for designing equivalent cost minimization strategies (ECMS) which achieve near optimal fuel economy (FE). The suggested approach makes use of the Pareto optimality criterion that exists in both ECMS and DP, and as such predicts the optimal equivalence factor for a drive cycle using DP marginal cost. The equivalence factor is then further modified with corrections based on battery SOC, with the aim of making the equivalence factor robust to drive cycle variations. Adaptive logic is also implemented to ensure battery charge sustaining operation at the desired SOC. Simulations performed on parallel and power-split HEV architectures demonstrate the cross-platform applicability of the DP-informed ECMS approach. Fuel economy data resulting from the simulations demonstrate that the robust controller consistently achieves FE within 1% of the global optimum prescribed by DP. Additionally, even when the equivalence factor deviates substantially from the optimal value for a drive cycle, the robust controller can still produce FE within 1–2% of the global optimum. This compares favorably with a traditional ECMS controller based on a constant equivalence factor, which can produce FE 20–30% less than the global optimum under the same conditions. As such, the controller approach detailed should result in ECMS supervisory controllers that can achieve near optimal FE performance, even if component parameters vary from assumed values (e.g., due to manufacturing variation, environmental effects or aging), or actual driving conditions deviate largely from standard drive cycles.

Development of Fuel Cell Hybrid Electric Vehicle Simulator and HCU

2010 ◽  
Vol 26-28 ◽  
pp. 1110-1114
Author(s):  
Dong Ji Xuan ◽  
Qian Ning ◽  
Zhen Zhe Li ◽  
Tai Hong Cheng ◽  
Yun De Shen
Keyword(s):  
Fuel Cell ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Cell Hybrid ◽  
Hybrid Electric Vehicle ◽  
Driver Model ◽  
Vehicle Speed ◽  
Battery Capacity ◽  
Hybrid Electric ◽  
Fuel Cell Hybrid

Based on the Matlab/Simulink module modeling for Fuel Cell Hybrid Electric Vehicle was carried out, which is comprised of the fuel cell stack model, a DC/DC converter model, a battery model, a motor model, avehiclemodel and a driver model, and Hybrid Control Unit(HCU) was developed. The HCU control strategy also incorporates regenerative braking and recharge for battery capacity recovery. Vehicle speed effect is evaluated in New Europe Driving Cycle. The simulation result that the control strategy implemented by HCU is achievable, and which proves that the mode of Start, Accele_FCBat, Cruise, RE_Brake, Power_FC and Pause operate sequently as well as reliably.

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