title: Energy and Service Life Management Strategy for a Two-Drive Multi-Speed Electric Vehicle
Creators: name: Tao, Yikai
Publisher: name: UNSPECIFIED
Year: 2024

description: Regulations of zero emission passenger cars appear on the horizon, and battery electric vehicles (BEV) are the main solution from the current market. It has been a focus of both academia and industry to extend their range. One of the main approaches is to reduce their energy consumption. Recent studies have shown that the two-drive topology and the multi-speed topology help to do so. It is natural to combine both concepts and to design a two-drive multi-speed topology for BEVs. Due to its more than one degree of freedom, an online energy management strategy (EMS) controlling torque set points of both electric motors and target gear positions is necessary to exploit its potential for reducing total energy consumption in real-world applications. There are numerous studies on EMSs for BEVs and hybrid electric vehicles. The overwhelming majority of them shared the same assumption: shift processes are neglectable. Based on the shift duration statistics, the shift processes of the most common transmissions in today’s market are too long to be ignored for an EMS with an operation frequency of at least 1 Hz. How to develop an EMS that considers shift processes? Suppose that an EMS is developed. It controls the powertrain in favour of low energy consumption, and the parts and the components are loaded accordingly. Some parts might fatigue and fail much faster than others, not because of poor construction dimensioning, but because of excessive use. What can an EMS do to prevent such an extreme scenario? Furthermore, is there a general way to design EMSs for multi-drive BEVs?
This thesis is initiated by developing an online EMS for a two-drive multi-speed BEV called “Speed4E”, and tends to address the questions raised earlier. A predictive EMS in a Model Predictive Control framework is developed. A hybrid system considering the shift processes is proposed. Based on it and the Hybrid Minimum Principle, a solver and its algorithms are developed. The Principle is chosen for its accuracy and low time complexity, the two most important attributes of an online EMS. Minimizing the instantaneous Hamiltonian in the Principle is mathematically analysed. Several Lemmas that reduce the time complexity considerably are produced. Compared to an EMS that minimizes instantaneous energy consumption and ignores shift processes, the predictive EMS reduces the energy consumption in the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) by 0.26 % and the shift count by 63.41 %. The hybrid system, the predictive EMS and the mathematical analysis are, as far as the author knows, first of their kinds. A novel multi-criteria operation strategy (MCOS) considering powertrain service life is proposed. Thanks to the hybrid system, the influence of the shift processes on fatigue is included. The MCOS extends the powertrain service life by several times but sacrifices the energy consumption. A general multi-drive (at least two) multi-speed electric powertrain is proposed. Its hybrid system is formulated. The Principle is applied to produce the optimality condition. It is showcased, how to modify certain sets and sample space in the formulation to have the general model and problem represent certain electric powertrains. A unified framework to design EMS for the general multi-drive electric powertrain is proposed, where the algorithms developed for the predictive EMS can be applied.