Range-extended Electric Bus Research Articles

Economic optimisation of range-extended electric bus based on AMGA algorithm

Economic optimisation of range-extended electric bus based on AMGA algorithm

Economic optimisation of range-extended electric bus based on AMGA algorithm

The power of a range-extended electric bus comes from its battery and range-extender. How to design the range-extender working point for the vehicle in the process of running is the key factor to achieve energy conservation and emission reduction. To solve this problem, a vehicle model was built by using AVL Cruise simulation software. Through Cruise and Isight co-simulation optimisation, a multi-objective optimisation model for per 100-km fuel consumption and pollutant emission is established. Optimal variables include upper and lower limits of the power unit and working point of the range-extender. Adaptive mutation genetic algorithm (AMGA) was used as optimisation algorithm. Results showed that fuel consumption and pollutant emissions were effectively reduced. The per 100-km fuel consumption decreased by 48.0%, carbon monoxide emission decreased by 49.6%, hydrocarbon emission decreased by 47.28%, and nitrogen oxide emission decreased by 51.1%. The economics of range-extended electric bus have been greatly improved.

Optimisation of control strategy of a range-extended electric bus

The aim of the present study was to optimise the cycle fuel consumption and energy consumption of a range-extended electric bus. The optimal variables included the final drive ratio of the main decelerator, the upper and lower limits of the power unit and the speed threshold. NSGA-II was used as the optimisation algorithm. The optimisation results showed that the overall economy behaviour of the bus was improved, while climbing performance increased by 43.77%. The stability of dynamic performances was acceptable and only slight fluctuations were found in the maximum speed and the acceleration duration from 0 km/h to 50 km/h. Although the power consumption increased by 0.6%, per 100 km fuel consumption decreased by 32.98%. The results showed that the optimisation strategies, optimisation objectives and optimisation variables applied in this paper were reasonable and effective.

Optimisation of control strategy of a range-extended electric bus

Optimisation of control strategy of a range-extended electric bus

Multi-objective optimization study of energy management strategy and economic analysis for a range-extended electric bus

A method of multi-objective optimal energy management is proposed to match the APU fuel consumption and the battery state of health (SOH) in the power system of a range-extended electric bus (REEB). Models are established for the calculation of an auxiliary power unit (APU) system fuel consumption and battery SOH loss. The APU fuel consumption and battery SOH are selected as the optimization objectives, and a performance functional of the multi-objective optimization is provided. The dynamic program (DP) algorithm is applied in the control strategy design for solving the multi-objective problem. Under the conditions of the Modified New European Drive Cycle (MNEDC) and Chinese Typical Urban Drive Cycle (CTUDC), which have been used to evaluate the performance of the proposed methodology, the matching-relation between SOH penalty coefficients of battery pack and APU fuel consumption, the SOH of a battery pack can be analysed. Taking the costs of a battery pack and fuel consumption in the whole life cycle as the comprehensive evaluation index, an optimization design method is proposed to match the capacity and the SOH of the battery pack. The simulation results show that when batteries do not need to be replaced, the best economical results will be achieved if the parameters of battery pack and the control strategy parameters are both taken the minimum.

Multi-objective Optimal Energy Management Strategy and Economic Analysis for an Range-Extended Electric Bus

An optimal energy management strategy is proposed to match engine fuel consumption and battery SOH of REEB. Models of APU fuel consumption and battery SOH loss are established and multi-objective performance function is provided. DP algorithm is adopted to solve the optimization problem. Under the conditions of different drive cycles, different SOH penalty coefficients are analyzed to reveal its effects. Considering the total life-cycle costs, simulations prove that when battery is not to be replaced, and the capacity configuration and SOH penalty coefficient of battery are both taken the minimum, the best economical results can be achieved.

Energy Efficiency Oriented Design Method of Power Management Strategy for Range-Extended Electric Vehicles

The energy efficiency of the range-extended electric bus (REEB) developed by Tsinghua University must be improved; currently, the energy management strategy is a charge-deplete-charge-sustain (CDCS) strategy, which exhibits low energy efficiency on the demonstration model. To improve the energy efficiency and reduce the operating cost, a rule-based control strategy derived from the dynamic programming (DP) strategy is obtained for the Chinese urban bus driving cycle (CUBDC). This rule is extracted by the power-split-ratio (PSR) from the simulation results of the dynamic powertrain model using the DP strategy. By establishing the REEB dynamic models in Matlab/Simulink, the control rule can be achieved, and the power characteristic of powertrain, energy efficiency, operating cost, and computing time are analyzed. The simulation results show that the performance of the rule-based strategy presented in this paper is similar to that of the DP strategy. The energy efficiency can be improved greatly compared with that of the CDCS strategy, and the operating cost can also be reduced.

Dynamic Programming-Based Energy Management System for Range-Extended Electric Bus

The heavy computational burden associated with the application of the traditional DP strategy to the energy management of range-extended electric buses poses a serious problem. On the basis of one Chinese typical urban bus driving cycle, an optimal control strategy is designed according to the SOC consumption trend, which is optimized by the DP algorithm. The dissipative energy and the energy-traction efficiency are our evaluation indices. The energy efficiencies of the powertrain system and components are analyzed by the energy flow diagram method. The results show that when the range-extended electric bus runs 35 Chinese typical urban bus driving cycles, the energy consumption and the energy efficiency of the powertrain system, which are optimized by the traditional DP strategy, can reach 2844.28 MJ and 31.29%, respectively. Compared with the traditional bus, the energy consumption can be reduced by 31.08%. The energy consumption and the energy efficiency of the powertrain system, which are based on one driving cycle optimal strategy, can reach 2857.69 MJ and 31.14%, respectively. The energy consumption is 0.47% higher than that with the traditional DP strategy, but the computation time is reduced by 96.85%.

Energy Efficiency and Economy Analysis of a Range-extended Electric Bus in Different Chinese City Driving Cycles

Based on establishing the powertrain simulation model of the range-extended electric bus, the selected driving cycles are Chinese city and Zhuzhou city of Hunan province, the energy efficiency and economy of the range-extended electric bus is simulated and analyzed with the energy management strategies of CD-CS and Blended. The simulation results show that, the energy efficiency and economy of the range-extended electric bus is different in different driving cycles. Compared with the conventional fuel bus, the energy efficiency is the highest with CD-CS strategy, cost saving can reach 32.81%.

Energy Flow Chart-Based Energy Efficiency Analysis of a Range-Extended Electric Bus

This paper puts forward an energy flow chart analysis method for a range-extended electric bus. This method uses dissipation and cycle energy, recycle efficiency, and fuel-traction efficiency as evaluation indexes. In powertrain energy efficiency analysis, the range-extended electric bus is developed by Tsinghua University, the driving cycle based on that of Harbin, a northern Chinese city. The CD-CS and blended methods are applied in energy management strategies. Analysis results show with average daily range of 200 km, auxiliary power of 10 kW, CD-CS strategy, recycle ability and fuel-traction efficiency are higher. The input-recycled efficiency using the blended strategy is 24.73% higher than CD-CS strategy, while the output-recycled efficiency when using the blended strategy is 7.83% lower than CD-CS strategy.