Interp1 function in ODE45 - ode45

Question

I am trying to solve a 3 Degree Of Freedom vessel-crane system in MATLAB using ode45. In my ode function, the vessel motion is determined by simple spring and damper constants, but the device below the main hoist system, a cranemaster, has a displacement-dependent stiffness and thus depends on one of the Degrees Of Freedom. To determine this value, I use the interp1 function to determine the stiffness from a dataset:
vq = interp1(x,v,xq,method,extrapolation)
This all works fine, but only when I add the extrapolation option in the interp1 function, even though the xq values all fall inside the dataset x-values. If I do not specify extrapolation, the function returns NAN.
I have checked if the stiffness values in the dataset make sense by taking the median value as a constant value and then the ode45 solver works just fine and the displacement never falls outside of the dataset. I have also noticed that if I switch to ode23 as a solver, it also works. This all makes me believe it has something to do with the solving method and the stepsize the ode solver takes as its initial value.
I have provided (a simplified version of) my code and a picture of the system to get a feel for the problem. I know that switching to ode23 solves the problem but I would like to understand why and, if possible, stay with ode45 as it is a more general solver.
Any help would be appreciated!
Regards,
Diederik
Overview of the system I am solving
close all
tspan = [0 100];
x0 = [0.0; 0; 0.0; 0; 0.0; 0]; % initial disp. and vel. is 0. for all 3 DOF.
% x = [z; zdot; theta; thetadot; u; udot]
[t,x] = ode45(#Three_DOF,tspan,x0);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Plots
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure()
subplot(2,1,1)
plot(t,x(:,5),'color','b','LineWidth',1)
grid on
xlabel('Time (s)')
ylabel('Displacement (m)')
title('Displacement Vs Time')
subplot(2,1,2)
plot(t,x(:,6),'color','#D95319','LineWidth',1)
grid on
xlabel('Time (s)')
ylabel('Velocity (m/s)')
title('Velocity Vs Time')
function [dxdt] = Three_DOF(t,x)
% vessel parameters
m = 570.5e6;
m55 = 4.591e12;
mh = 200e3;
c33 = 3.83952e8;
c55 = 3.66116e12;
wnh = 0.360;
wnp = 0.596;
a33 = (c33-wnh^2*m)/wnh^2;
a55 = (c55-wnp^2*m55)/wnp^2;
zeta33 = 0.386;
zeta55 = 0.121;
b33 = zeta33*2*sqrt(c33*(m+a33));
b55 = zeta55*2*sqrt(c55*(m55+a55));
Fa = 153e6;
Ma = 3.013e9;
w1 = 0.21/0.36;
w2 = 0.18/0.28;
%%%% Cable parameters
k_c = 496e6;
b_c = 5.01e6;
%%% CRANEMASTER parameters
x_data = [-2.0; -1.87; -1.73; -1.60; -1.47; -1.33; -1.20; -1.07; -0.93; -0.8; -0.67; -0.53; -0.4; -0.27; -0.13; 0.0; 0.13; 0.27; 0.40; 0.53; 0.67; 0.80; 0.93; 1.07; 1.20; 1.33; 1.47; 1.60; 1.73; 1.87; 2.0];
k_data = [760; 792.1; 784.8; 813.9; 828.4; 850.2; 879.3; 901.1; 922.9; 959.2; 981.0; 1010.1; 1039.1; 1068.2; 1104.5; 1133.6; 1177.2; 1206.3; 1242.6; 1286.2; 1329.8; 1373.4; 1409.7; 1460.6; 1511.5; 1562.3; 1620.5; 1671.3; 1729.5; 1794.9; 1853];
k_cm = 30000*interp1(x_data,k_data,x(5));%,'linear','extrap');
%k_cm = 30000*1133.61; % middle value of dataset k_data
b_cm = 6e4;
l = 217.5;
% Matrices & solve
Mass = [m+a33 0 0; 0 m55+a55 0; 0 0 mh];
k = [c33+k_c -k_c*l -k_c; -k_c*l c55+k_c*l^2 k_c*l; -k_c k_c*l k_c+k_cm];
b = [b33+b_c -b_c*l -b_c; -b_c*l b55+b_c*l^2 b_c*l; -b_c b_c*l b_c+b_cm];
F = [Fa*sin(w1*t); Ma*sin(w2*t); 0];
EOM = Mass\(F-b*([x(2); x(4); x(6)])-k*([x(1); x(3); x(5)]));
dxdt = [x(2); EOM(1); x(4); EOM(2); x(6); EOM(3)];
% x = [z; zdot; theta; thetadot; u; udot]
end