In Mathematics the Lyapunov exponent of a dynamical systems is a quantity that characterizes the rate of separation of infinitesimally close trajectories. Is there some new algorithms for calculate the Lyapunov exponent?
In the Taylor series then you can find the vector \lambda up to the order you want. Numerical Taylor methods... suggest a procedure you may follow for this multivariable function. It is an idea. Apply chain rule to obtain the nonlinear system of equations on \lambda_i.
The Taylor series is for your ODE in the left side. The right side is the multiple polynomials in \lambda up to the grade you want to solve. Then in the limit t \arrow 0 it becomes in a system of nonlinear equations in \lambda.
As for calculating the Lyapunov exponent from the time series (without knowing the exact form of the underlined system behind), I suggest to refer to the algorithms developed in the seminal paper by A. Wlof et al., published in Physica D (1985, 16, pp. 285). As for calculating the exponent from a deterministic dynamical systems, one can directly compute it according to the typical definition, which could be found through the Wikipedia.
If you are looking for algorithms to approximate Lyapunov exponents of nonlinear differential equations, other than those already recommended, you can read
1. Luca Dieci, Jacobian free computation of Lyapunov exponents.
2. K. Ramasubramanian, M.S. Sriram, A comparative study of computation of Lyapunov spectra with different algorithms
Lots of people just plot a projection of the trajectory in some 2-D space, and if it looks scrambled, they declare that the system is chaotic, and they are usually correct. However, if you do this, iterate the equations for quite a while before you begin plotting the results since chaotic transients are quite common for systems that eventually attract to a limit cycle or stable equilibrium point. If you plan to publish your claim of chaos in a reputable journal, you really need to show that the largest Lyapunov exponent is positive and statistically significant.