**2. MOO Design Method of EHA**

For the design of systems with high integration and complex structure, such as EHA actuation systems, choosing the design parameters to get a satisfactory performances is a difficult task, as there ae typically many objectives to be considered, such as light weight, high energy efficiency, good dynamic performance, and stiffness. Furthermore, these objectives usually conflict with each other. This is a MOO problem which usually needs a method to find the Pareto front of all the objectives intelligently.

Modeling and simulation are important tools in modern design, which can obtain the performances quickly by using a computer. There are some powerful modeling and simulation tools for electrical and hydraulic system design, such as AMESim. In AMESim, an EHA system can be modeled and simulated, with high precision and without too much effort. However, setting and optimizing the parameters is a daunting task, since there are a number of parameters which should be decided and the engineer has to go through a lot of simulation curves to judge the performances, which usually needs expert experience and takes a lot of labor time. If the model calculation does not obtain an ideal control state, the designer needs to find the improper parameters and simulate again and again, until the results are satisfactory. However, a "satisfying" result is usually not the optimal solution, since the designer can not continue to optimize the parameters for a long time. In summary, the manual simulation-based design methods rely on the experience of the designer and increases the time cost of system development. Obviously, the traditional approach to designing EHA is outdated, in the current era of "automation and intelligence". Therefore, improving design efficiency is a problem for these highly complex system design methods.
