A Bi-stable Piezoelectric Energy Harvester With A Variable Potential Function Under Parametric Excitation And Its Optimization

With the development of MEMS technology,it has become research hotspot to convert vibration energy in the environment into electrical energy to supply the power for electronic devices.Among them,the piezoelectric energy harvester has attracted wide attention.Although bi-stable piezoelectric energy harvester,as a typical energy harvester,has been studied extensively at present,they have some defects,such as higher potential barrier.In addition to this,there is few work focusing on bi-stable energy harvesters under the parameter excitation.In order to overcome the higher potential barrier,expand the energy harvesting bandwidth and increase the energy output of the harvester,a two-degrees-of-freedom bi-stable piezoelectric energy harvester with variable potential function is proposed in this thesis.The energy harvester is composed of a vertical beam and a spring-magnet block fixed on the base.One end of vertical beam is also fixed on the base,and the other end with magnet is free.The system can be in bi-stable state by adjusting the initial distance between magnets.The main work of this thesis includes the derivation of dynamics equation of the system with extended Hamiltonian principle,studies on the potential function of the system,and the influence of system parameters on system dynamics and energy harvesting performance under both the harmonic and random excitation,the optimization of the system parameters taking the root mean square voltage as the objective function is conducted.The main conclusions of the studies are as following:1.With the introduction of the variable potential energy function,the piezoelectric beam will traverse different potential energy function curves during the vibration motion.As it reaches the potential energy function curve with a lower barrier,the bi-stable system will easily break away from the unilateral potential well and oscillate between the wells,which increase the output of system.The motion of the spring-magnet block causes the varition of the magnetic potential energy,which is the main factor for the potential energy varying.The increasing in the displacement of spring-magnet block has an effect on suppressing the potential barrier.2.It is shown that under harmonic excitation,the constitution of the harvester with variable potential function makes it easier to realize the motion between the potential wells even at low excitation amplitude;With different parameters of the system,the harvester exhibits different motion,such as small periodic intra-well motion,small chaotic inter-well motion,large chaotic inter-well motion and large periodic intra-well motion etc.The highest value of the output power of the system is achieved only when the motion between the wells is chaotic,and the parameters for the chaotic motion are a special combination and should be selected carefully.With the increasing of excitation amplitude,the small-amplitude periodic intra-well motion will be transformed into the chaotic inter-well motion;There is an optimal value of external load corresponding to specific excitation frequencies;the system parameters are optimized by the genetic algorithm to generate a higher voltage output for specific excitation frequency.3.For the random excitation,the Gaussian white noise is taken as the excitation for the comparing the dynamics performances between variable potential function harvester and non-variable potential function harvester.It is shows that the bi-stable system with a variable potential function can generate random jumps between potential wells even when the noise intensity is lower.If the noise intensity is large enough,coherent resonance of the system will occur timely,which will increase the output of system.With the increasing of the noise intensity,the number of jumps between the potential wells will increase,and consequently the output voltage increases;For the variable potential function harvester,there is also a best value of resistance under random excitation,and the value will increase with increasing of the noise intensity;the system parameters are optimized by genetic algorithm in order to generate a higher voltage output with the specific noise intensity.