A model-predictive-control-based power management strategy for a power-split electromechanical transmission

Abstract

A power management strategy is a key necessity for power-split electromechanical transmission systems. A model predictive control strategy which is based on finite-horizon optimization and can combine the advantages of instantaneous optimization and global optimization is a good solution for online optimization of the power management. Therefore, a model-predictive-control-based power management strategy is proposed for a two-mode electromechanical transmission. A model predictive control strategy consists of two parts: a predictive model and a receding-horizon optimization algorithm. A predictive model is used for predicting future information on the electromechanical transmission states, and real-time receding-horizon optimization with a finite horizon is adopted for optimal decision making. First, the predictive model, including the battery state and the transmission output torque, which provides a priori knowledge for optimal calculation, is proposed. Then, to ensure optimal operating areas of the engine and the motors, a novel overall efficiency calculation method for the whole powertrain including the engine, the motors, the power-split coupled machine and the battery is proposed and regarded as the optimization objective. The overall efficiency not only is focused on the engine fuel economy but also determines the power loss of the motors, the battery and the planetary gears together, which enhances the fuel economy and the transmission efficiency significantly. Based on the predictive model and receding-horizon optimization, the MPC strategy is established and tested by hardware-in-the-loop simulations under Urban Dynamometer Driving Schedule and New European Driving Cycle conditions. The test results showed that the power management strategy can enhance the fuel economy and proved to be a potential real-time optimization method for power distribution in the electromechanical transmission system; this strategy can provide theoretical support for actual application of electromechanical transmission systems.

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

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

“…The battery pack model is an equivalent circuit with an internal resistance, and the battery pack's internal resistance can be obtained from the experimental data, as shown in Figure 5. The equivalent circuit and SOC of the battery can be given by the following equations [7]:…”

“…It is noted that when P ele > 0, it represents the consumed electrical power of the MGs, and thus the engine and the battery, as the vehicle's power sources, transfer the power to the wheel based on the dashed line direction; when P ele < 0, the generated electrical power of the MGs stores in the battery, and thus the engine provides the only power source to drive the vehicle based on the solid line direction. The detailed description of the overall efficiency calculation for the hybrid HDV with PST can be found in the previous research work [7,34]. method is also used to design a two-parameter economic shift schedule (throttle opening and vehicle speed) of the hybrid HDV with PST.…”

“…Moreover, MGs can coordinate engine starting and stopping while the vehicle is running [4,5]. Furthermore, PST combines with a relatively small number of frictional elements, including clutch and brake, such that the transmission enables the vehicle at high efficiencies and meets the special requirements of the hybrid heavy-duty vehicle (HDV), such as wide speed range and large power of the MGs [6,7]. 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.…”

Adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for four-wheel drive hybrid electric vehicles

“…Musardo et al, 11 Pisu and Rizzoni, 12 and Wang et al 13 proposed several types of adaptive equivalent fuel consumption minimisation strategy (A-ECMS) to distribute the energy of the engine and the motor by using different methods to self-adaptive adjust equivalent factors online according to the current operating conditions and to ensure that the equivalent fuel consumption is minimised on the premise of maintaining the balance of battery power. Wang et al 14 proposed a model-predictive-control-based power management strategy for a power-split electromechanical transmission. Xiang et al 15 proposed an energy management strategy based on a non-linear model predictive control algorithm and velocity prediction for a dual-mode power-split HEV.…”