Dynamic Modeling and Control of an Hybrid Electric Powertrain for Simulation Under Transient Conditions

2009 ◽  
Author(s):  
Ronan Crosnier ◽  
Jean-Franc¸ois Hetet
Keyword(s):  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Power Stroke ◽  
Engine Fuel ◽  
Energy Management Strategy ◽  
Modeling And Control ◽  
Engine Torque ◽  
Hybrid Electric ◽  
And Control ◽  
Engine Map

This article presents a causal, forward looking approach for the hybrid electric vehicle where the typical performance engine map representation has been modified. The need for a more physical model of the power stroke process has been fulfilled with “the filling and emptying” method. The thermodynamic states in the intake and exhaust systems are calculated, while the in-cylinder process is still based on the engine fuel consumption map as a calibrated data. Comparisons with the conventional model are established, most important is the response of the engine torque under the load demand. This notion of an “available” torque is taken into account by the energy management strategy. Changes on the distribution of energy flow in order to meet the required torque at the wheel are observed and influence of this modelisation on the fuel consumption over various driving cycles is evaluated.

Stirling system optimization for series hybrid electric vehicles

2021 ◽  
pp. 095440702110180
Author(s):  
Charbel R Ghanem ◽  
Elio N Gereige ◽  
Wissam S Bou Nader ◽  
Charbel J Mansour
Keyword(s):  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimization Technique ◽  
System Optimization ◽  
Energy Management Strategy ◽  
Fuel Savings ◽  
Auxiliary Power ◽  
Hybrid Electric ◽  
External Combustion

There have been many studies conducted to replace the conventional internal combustion engine (ICE) with a more efficient engine, due to increasing regulations over vehicles’ emissions. Throughout the years, several external combustion engines were considered as alternatives to these traditional ICEs for their intrinsic benefits, among which are Stirling machines. These were formerly utilized in conventional powertrains; however, they were not implemented in hybrid vehicles. The purpose of this study is to investigate the possibility of implementing a Stirling engine in a series hybrid electric vehicle (SHEV) to substitute the ICE. Exergy analysis was conducted on a mathematical model, which was developed based on a real simple Stirling, to pinpoint the room for improvements. Then, based on this analysis, other configurations were retrieved to reduce exergy losses. Consequently, a Stirling-SHEV was modeled, to be integrated as auxiliary power unit (APU). Hereafter, through an exergo-technological detailed selection, the best configuration was found to be the Regenerative Reheat two stages serial Stirling (RRe-n2-S), offering the best efficiency and power combination. Then, this configuration was compared with the Regenerative Stirling (R-S) and the ICE in terms of fuel consumption, in the developed SHEV on the WLTC. This was performed using an Energy Management Strategy (EMS) consisting of a bi-level optimization technique, combining the Non-dominated Sorting Genetic Algorithm (NSGA) with the Dynamic Programming (DP). This arrangement is used to diminish the fuel consumption, while considering the reduction of the APU’s ON/OFF switching times, avoiding technical issues. Results prioritized the RRe-n2-S presenting 12.1% fuel savings compared to the ICE and 14.1% savings compared to the R-S.

Hierarchical energy management strategy considering switching schedule for a dual-mode hybrid electric vehicle

2021 ◽  
pp. 095440702110297
Author(s):  
Hui Liu ◽  
Rui Liu ◽  
Riming Xu ◽  
Lijin Han ◽  
Shumin Ruan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Power Distribution ◽  
Hybrid Electric Vehicle ◽  
Hierarchical Control ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Dual Mode ◽  
Hybrid Electric

Energy management strategies are critical for hybrid electric vehicles (HEVs) to improve fuel economy. To solve the dual-mode HEV energy management problem combined with switching schedule and power distribution, a hierarchical control strategy is proposed in this paper. The mode planning controller is twofold. First, the mode schedule is obtained according to the mode switch map and driving condition, then a switch hunting suppression algorithm is proposed to flatten the mode schedule through eliminating unnecessary switch. The proposed algorithm can reduce switch frequency while fuel consumption remains nearly unchanged. The power distribution controller receives the mode schedule and optimizes power distribution between the engine and battery based on the Radau pseudospectral knotting method (RPKM). Simulations are implemented to verify the effectiveness of the proposed hierarchical control strategy. For the mode planning controller, as the flattening threshold value increases, the fuel consumption remains nearly unchanged, however, the switch frequency decreases significantly. For the power distribution controller, the fuel consumption obtained by RPKM is 4.29% higher than that of DP, while the elapsed time is reduced by 92.53%.

scholarly journals Research on energy management strategy considering battery life for plug-in hybrid electric vehicle

2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879776 ◽  
Author(s):  
Jianjun Hu ◽  
Zhihua Hu ◽  
Xiyuan Niu ◽  
Qin Bai
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Battery Life ◽  
Energy Management Strategy ◽  
Driving Cycles ◽  
Comprehensive Test ◽  
Hybrid Electric

To improve the fuel efficiency and battery life-span of plug-in hybrid electric vehicle, the energy management strategy considering battery life decay is proposed. This strategy is optimized by genetic algorithm, aiming to reduce the fuel consumption and battery life decay of plug-in hybrid electric vehicle. Besides, to acquire better drive-cycle adaptability, driving patterns are recognized with probabilistic neural network. The standard driving cycles are divided into urban congestion cycle, highway cycle, and urban suburban cycle; the optimized energy management strategies in three representative driving cycles are established; meanwhile, a comprehensive test driving cycle is constructed to verify the proposed strategies. The results show that adopting the optimized control strategies, fuel consumption, and battery’s life decay drop by 1.9% and 3.2%, respectively. While using the drive-cycle recognition, the features of different driving cycles can be identified, and based on it, the vehicle can choose appropriate control strategy in different driving conditions. In the comprehensive test driving cycle, after recognizing driving cycles, fuel consumption and battery’s life decay drop by 8.6% and 0.3%, respectively.

Real-Time Modeling, Simulation, and Control System Design of a Dual Hybrid Electric Vehicle

1999 ◽  
Author(s):  
Veronika Gospodareva ◽  
William Hamel ◽  
Claudell Hatmaker ◽  
Jeffrey Hodgson ◽  
Stephen Jesse ◽  
...  
Keyword(s):  
Control System ◽  
System Design ◽  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Control System Design ◽  
Modeling And Control ◽  
Hybrid Electric ◽  
And Control

Abstract The Graduate Automotive Technology Education (GATE) Center at the University of Tennessee, Knoxville (UTK) offers courses addressing the simulation, modeling, and control system design of hybrid electric vehicles (HEV). In the Spring of 1999 such a course was conducted to support the UTK FutureCar Challenge entry for 1999. The vehicle modeled is a Dual-configuration Hybrid Electric Vehicle (DHEV) which uses a planetary power-split device similar to the Toyota Hybrid System used in the Toyota “Prius”. The goals of the course included the development of a real-time simulator that could incorporate actual vehicle control hardware in the simulator loop. This “control-hardware-in-the-loop” (CHIL) configuration was used for simulation, control system design, and troubleshooting. This approach allows the simulation of normal vehicle operating conditions as well as emergency fault handling situations in which it may not be desirable to subject the actual prototype vehicle to a given test condition. Additionally, it is possible to do a great deal of control system testing and development without an operating vehicle.

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