Motion Coordination of BEV vehicles, how to maximise brake blending and still remain in control envelope during winter conditions
Battery Electric Vehicles (BEV) such as e-trucks, are going to conduct 95% of their soft and medium retardation by rear axle’s electric machines. This to maximize the regenerative power back to charge the battery during braking scenarios. During winter conditions the electric machine braking will cause lateral instability if the braking is taking too much of the available tyre friction circle the stabilizing lateral forces might be jeopardized.
Fig. 1. Regenerative braking on e-axle causing oversteer situation during low tyre/road friction.
In this thesis the brake blending of single unit is studied and what is preferred limits on rear axle for regenerative braking during low and medium road friction conditions.
The motion coordinator within the motion control system uses control allocator. The requested global forces and yaw moment (Fx, Fy, and yaw moment Mz) for the heavy vehicle and how the actuators are coordinated to achieve the request is solved by using Control Allocation (CA) within the heavy vehicle’s motion control system and in the engine control system, see Fig. 2. Control allocation is an option for coordination when the system has more input signals u∈R^m than virtual signals controlled v∈R^k, k
Fig. 2. Control system including a control allocator to distribute the desired virtual control input v (global force request) to the true control input u (device request).
One promising optimization method for mapping is the constrained mixed optimization formulation
u=〖argmin‖W_u (u_des-u)‖〗_p^p+γ‖W_v (Bu-v)‖_p^p
"subject to " ▁u≤u≤¯u
where B(x,u) is the control effectiveness matrix, Wu and Wv are diagonal weighting matrices, and γ is scalar weighting parameter to allow different priority between the mapping error Bu-v compared with error in desired signal error udes-u. When p is set to 2, the problem becomes to be a weighted least squares formulation.
The purpose of this master thesis contains of three parts:
1. Derive re-generative braking limits for rear e-axle braking on low and medium friction for different wheelbases, loading cases, and curvatures.
2. Show how balancing of brake blending of e-axles and service brakes should be conducted from -1 m/s2 to -5 m/s2 and formulate the control allocation problem.
3. Simulate winter tests for regenbraking of e-truck single unit with high fidelity vehicle model and conduct physical experiments in e-truck.
The thesis work will include control theory and real time optimization. The work will be carried out at Volvo Group Trucks Technology. The thesis is recommended for one or two students with control analysis profile with good mathematical skills. Thesis start: Jan 2022.
If you find this proposal interesting, send your application with CV and grades to:
Esteban Gelso – Volvo GTT
tel: +46 31 3227882
Jose Vilca – Volvo GTT
tel: +46 31 3223466
Leo Laine – Volvo GTT
tel: +46 31 323 5311
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