Energy management of a dual-mode power-split hybrid electric vehicle based on velocity prediction and nonlinear model predictive control

Chen, Xiang; Ding, Feng; Wang, Weida; Wei, He

doi:10.1016/j.apenergy.2016.12.056

Cited by 204 publications

(96 citation statements)

References 38 publications

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“…During each segment k, all the reachable states within the constraints form the collection S(k) and all the possible controls form the collection V(k), naturally as s(k) ∈ S(k) and v(k) ∈ V(k). According to Bellman's principle of optimality, the dynamic recursive equation to solve the best fuel consumption as illustrated in formula (18) can be expressed as…”

Section: Dp Equationmentioning

confidence: 99%

Real‐time implementation of optimal control considering gear shifting and engine starting for parallel hybrid electric vehicle based on dynamic programming

Song

et al. 2017

Optim Control Appl Methods

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Summary To achieve best fuel economy control for a parallel hybrid electric vehicle, optimized control based on dynamic programming (DP) is proposed. The main effort in this paper includes the following. First, the global optimal control mathematic model of the best fuel economy is constructed and its corresponding recursive equation is established. Second, 2 additional augmented cost functions are proposed to prevent frequent gear shifting and frequent engine stopping and starting. Third, an algorithm of restricting the exploring region is proposed to overcome the curse of dimensionality of the numerical DP, which can greatly reduce the computational complexity. Both this DP method and a simple threshold control in corporation of a standby optimization are applied to a vehicle manufactured by the Changan company on the Federal Test Program driving cycle. The results show that the proposed method is effective in reducing fuel consumption by 15%. Although the proposed DP method is implemented on a priori known driving cycle, it can provide a criterion to design and evaluate a control strategy to achieve better fuel consumption.

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Section: Dp Equationmentioning

confidence: 99%

Real‐time implementation of optimal control considering gear shifting and engine starting for parallel hybrid electric vehicle based on dynamic programming

Song

et al. 2017

Optim Control Appl Methods

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“…This will have disasterous results to the national economy and national security [6]. Therefore, the modern power network must use advanced monitoring, control and scheduling mechanism to maintain its stability and optimal operation.…”

Section: Paper-power Load Forecasting Based On Wireless Sensor Networkmentioning

confidence: 99%

Power Load Forecasting Based on Wireless Sensor Networks

Liu

Li²

2017

Int. J. Onl. Eng.

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Abstract-At present, wireless sensor networks (WSN) technology is a field of much research interest in the area of information technology. The application of wireless sensor networks is expected to be very broad. With the development of communication protocol and their corresponding components, wireless sensor networks technology plays an increasingly important role in the power industry. The analysis and forecast of electric power data is essential to the construction and operation of the power network. Through the wireless sensor networks, we can obtain comprehensive power data. Then we can better forecast the power load through the data we obtain from the wireless sensor networks. In this paper, we propose an improved LSSVM method. We collect the power data by the wireless sensor networks and use the improved LSSVM method to forecast the power load. Experimental results demonstrate the effectiveness of the proposed method. Keywords-LSSVM; WSN; power data IntroductionWith the advent of wireless sensor networks, networking and intelligent information gathering technology replace the independent single model. Wireless sensor networks have become an important research focus in the IT field [1-2].Power energy is the primary energy supply form in modern society. Power systems has become a lifeline for the whole society [3][4]. With the development of the national economy, the demand for electricity in both urban and rural areas is increasing in China contiguously. By the end of the year 2016, Chinese annual electricity generation was 5 trillion and 920 billion kw/h, ranking first in power output globally.The production, transmission and use of electric energy constitute a complex, timevarying and stochastic dynamic process. As such, the enormous energy demands must be distributed and consumed by the facilities of power generation, transmission and distribution to numerous users [5]. 86http://www.i-joe.org Paper-Power Load Forecasting Based on Wireless Sensor NetworksAny fault in the power network may cause a chain reaction and may result in collapse. This will have disasterous results to the national economy and national security [6]. Therefore, the modern power network must use advanced monitoring, control and scheduling mechanism to maintain its stability and optimal operation. The expansion of the power network to accomidate the increasing demand will lead to the continuous improvement in the automation level of power network management and automatic level of operation [7][8].In the power system automation field, the existing research applies the wireless sensor networks to remote meter reading [9], substation automation [10], transmission line real-time monitoring [11] and early warning [12], etc. At the same time, the data collected by the wireless sensor networks can also be used to forecast the power load and provide a powerful guarantee for the electrical needs of both daily life of the society and industry.The least squares support vector machine replaces the inequality constraints of standard support vect...

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“…Therefore, the speed and the torque relationships of EVT Mode 1 based on Figure 4a can be written as follows [7,14]:…”

Section: Speed Equations and Torque Equationsmentioning

confidence: 99%

“…In this paper, the MG is modeled by its efficiency characteristic, and the MG efficiency can be described as a function of the MG speed and the torque. The MG power can be expressed by the mechanical power, the electrical power, and the power loss as [14]:…”

Section: Motor-generator Modelmentioning

confidence: 99%

“…In this regard, the application of the hybrid HDV with PST is readily adaptable to the commercial market and the agricultural market, such as a bulldozer or a heavy truck for mining. Given the excellent characteristics of the power-split HEV, to explore and develop the analysis method, design theory, and control strategy of such a system, previous research studies on the power-split HEV have put forward different operating strategies in terms of fuel consumption by a neural network [8], rule-based supervisory control [9], optimal control [10], multi-input fuzzy logic controller [11], multivariable coordination controller [12], quadratic programming [13], and nonlinear model predictive control [14].…”

Section: Introductionmentioning

confidence: 99%

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Mode Shift Control for a Hybrid Heavy-Duty Vehicle with Power-Split Transmission

Huang

Chen

et al. 2017

Energies

Self Cite

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Given that power-split transmission (PST) is considered to be a major powertrain technology for hybrid heavy-duty vehicles (HDVs), the development and application of PST in the HDVs make mode shift control an essential aspect of powertrain system design. This paper presents a shift schedule design and torque control strategy for a hybrid HDV with PST during mode shift, intended to reduce the output torque variation and improve the shift quality (SQ). Firstly, detailed dynamic models of the hybrid HDV are developed to analyze the mode shift characteristics. Then, a gear shift schedule calculation method including a dynamic shift schedule and an economic shift schedule is provided. Based on the dynamic models and the designed shift schedule, a mode shift performance simulator is built using MATLAB/Simulink, and simulations are carried out. Through analysis of the dynamic equations, it is seen that the inertia torques of the motor-generator lead to the occurrence of transition torque. To avoid the unwanted transition torque, we use a mode shift control strategy that coordinates the motor-generator torque to compensate for the transition torque. The simulation and experimental results demonstrate that the output torque variation during mode shift is effectively reduced by the proposed control strategy, thereby improving the SQ.

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Energy management of a dual-mode power-split hybrid electric vehicle based on velocity prediction and nonlinear model predictive control

Cited by 204 publications

References 38 publications

Real‐time implementation of optimal control considering gear shifting and engine starting for parallel hybrid electric vehicle based on dynamic programming

Real‐time implementation of optimal control considering gear shifting and engine starting for parallel hybrid electric vehicle based on dynamic programming

Power Load Forecasting Based on Wireless Sensor Networks

Mode Shift Control for a Hybrid Heavy-Duty Vehicle with Power-Split Transmission

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