Sliding mode based powertrain control for efficiency improvement in series hybrid-electric vehicles

Gökaşan, Metin; Boğosyan, Seta; Goering, Douglas J.

doi:10.1109/tpel.2006.872373

Cited by 108 publications

(37 citation statements)

References 22 publications

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“…The 10 kW, 15 kW and 20 kW power isolines are also shown in Figure 4. (3) A specific power value [7,20], that is P cmd = P set . In this case, the independent variables (n, T) are located on the power isoline P set and must fulfill the following equation:…”

Section: Constraintsmentioning

confidence: 99%

“…He and Yang [6] proposed a robust linear parameter-varying (LPV) method which attempts to optimize the APU fuel efficiency through stabilize the APU working point at the maximum efficiency region. Gokasan et al [7] proposed a novel approach in the optimization of APU fuel efficiency. Two chattering-free sliding-mode controllers (SMCs) were developed to keep the engine operating in the optimal efficiency region.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Shen

Liu

et al. 2016

Energies

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Auxiliary power units (APUs) are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP) firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC) emissions, carbon monoxide (CO) emissions and nitric oxide (NO x ) emissions. Then, the multi-objective particle swarm optimization (MOPSO) algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC), Federal test procedure (FTP) and high way fuel economy test (HWFET) driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

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Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Shen

Liu

et al. 2016

Energies

View full text Add to dashboard Cite

show abstract

“…Although this structure is a low cost solution, the electrical excitation machine does not meet the requirements of high power density in EV applications [3][4][5][6]. The other form is composed of a PMSG and PWM rectifier, which can control both the generator operating in motor state and the generator state [7][8][9]. This form features a simple structure, high power density and synchronous control of engine speed and motor torque, so it's an ideal solution.…”

Section: Introductionmentioning

confidence: 99%

“…As the current loop of PMSG control with coupled dq current, it had to add a compensation to improve the dynamic performance, which leads control structure complexity and a lack of robustness. Some references also designed robust, for instance, in [8], a global efficiency optimization of sliding mode control is proposed, in which two chattering-free sliding mode controllers are utilized to control engine speed and PMSG torque; in [12,13], adopts a fuzzy logic control; in [14][15][16] a Dynamic Programming (DP) technology is used to obtain an optimal solution. However, these control strategies such as DP algorithm are not suitable for EREV real-time control; because they are based on masses of driving cycle and a lot of data processing.…”

Section: Introductionmentioning

confidence: 99%

A Proportional Resonant Control Strategy for Efficiency Improvement in Extended Range Electric Vehicles

Wang

Sun

et al. 2017

Energies

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Abstract:The key to control the range extender generation system is to improve the efficiency and reduce the emissions of the electric vehicle (EV). In this paper, based on the purpose of efficiency optimization, both engine and generator are matched to get a public high efficiency region, and a partial power following control strategy was presented. The engine speed is constant in the defined power range, so the output power regulation of the range extender is only realized by the adjustment of the torque of the generator. Engine speed and generator torque were decoupled. An improved proportional resonant (PR) controller is adopted to achieve fast output power regulation. In order to ensure the response characteristics of the control system and to improve the robustness, the impacts on system's characteristics and stability caused by PR controller and parameters in the inner-current loop were analyzed via frequency response characteristics. A pre-Tustin with deviation compensation is proposed for PR controller's discretization. A stable and robust power following control method is obtained for the range extender control system. Finally, simulation and experiment of the proposed control strategy illustrated its feasibility and correctness.

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“…Gokasan et al [11] used sliding mode control to limit the series HEVs to the optimal efficiency operating range and compared it to PI controllers. They used two simultaneous sliding mode controllers one to control the engine speed, and the other to control the engine torque.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Energy Management Control for Hybrid Electric Powertrains

Zaher

Cetinkunt

2013

Journal of Control Science and Engineering

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This paper focuses on embedded control of a hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real-time energy management strategy. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in the opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, the motion is driven by gravitational force, or load driven. There are three main concepts for energy storing devices in hybrid vehicles: electric, hydraulic, and mechanical (flywheel). The real-time control challenge is to balance the system power demands from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle. In the worst-case scenario, only the engine is used and the hybrid system is completely disabled. A rule-based control algorithm is developed and is tuned for different work cycles and could be linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the work machine and its position via GPS and maps both of them to the gains.

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Sliding mode based powertrain control for efficiency improvement in series hybrid-electric vehicles

Cited by 108 publications

References 22 publications

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

A Proportional Resonant Control Strategy for Efficiency Improvement in Extended Range Electric Vehicles

Real-Time Energy Management Control for Hybrid Electric Powertrains

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