Fuzzy prediction control strategy of EMS with energy hybridization of high energy and high power
A combination of different electric energy supply with different feature is designed for high acceleration and high ranges and improves the whole system properties. Energy supply system with energy hybridization of high energy and high power need an intelligent management system in order to control power and state of charge. In this paper we proposed a fuzzy prediction control strategy of energy management system (EMS) based on a new forward-looking and causal structure model. This control strategy is mainly consisted of three controllers, including SOC prediction controller, recharge controller and power allocation controller. Simulation result shows that the driving range, the fuel economy and efficiency of fuzzy prediction control strategy have rapidly improvement compared with simple allocation (look-up table) control strategy. In the next step we will apply this control strategy with actual EV through "dspace autobox".
A new model for trust mechanism in E-commerce by introducing concept of ESS equilibrium, which includes a game-theory study of trust in E-commerce was provided, including a process of trust diffusion and its algorithm. The model finds that an incomplete credit system leads to prevalent distrust behaviors in E-commerce deals and some factors, like the number of traders choosing trust strategy, convenience of information exchange between traders and payoff difference between honest traders and dishonest traders, determine diffusion of trust in this business. The simulation experiment shows the model improves credibility and fidelity of the trust analysis for E-commerce trade through overcoming the existing shortcomings of static study. Finally, we suggested some policies including reinforcing trust incentives, increasing comparative advantage in payoff received by honest traders and investing more in information exchange technology, etc.