Hybrid Electric Vehicles (HEVs) can be divided into three categories according to how the two propulsion systems (the thermal and the electric ones) supply the driving torque to the vehicle. When the torque is supplied only by an electric propulsion system, while the heat engine takes care of generating the electricity needed to operate the system, it is called a hybrid-series. Conversely, when both propulsion systems provide torque, the vehicle is identified with parallel hybrid wording. Among the parallel hybrids there is a particular configuration called Through-the-Road (TTR). In this configuration, the two propulsion systems are not mechanically connected to each other, but it is precisely the road that allows hybrid propulsion. This architecture, dating back to the early twentieth century, is still used by several manufacturers and carries with it peculiar configurations and control methods. It is also a configuration that fits well with the transformation of conventional vehicles into a hybrid. The paper presents a survey of the TTR HEV solution, evidencing applications, potentialities and limits.

Regenerative braking can significantly improve the energy efficiency of hybrid and electric vehicles, and many studies have been carried out in order to improve and optimize the energy recovery of the braking energy. In the paper, the optimization of regenerative braking by means of braking force modulation is analysed, with specific application to the case of cars converted into Through-the-road (TTR) hybrid vehicles, and an optimal modulation strategy is also proposed. Car hybridization is an emerging topic since it may be a feasible, low-cost, intermediate step toward the green transition of the transport system with a potential positive impact in third-world countries. In this case, the presence of two in-wheel-motors installed on the rear axle and of the original mechanical braking system mounted on the vehicle can result in limited braking energy recovery in the absence of proper braking management strategies. A vehicle longitudinal model has been integrated with an algorithm of non-linear constrained optimization to maximize the energy recovery for various starting speed and stopping time, also considering the efficiency map and power limitations of the electric components. In the best conditions, the recovery can reach about 40% of the vehicle energy, selecting the best deceleration at each speed and proper modulation, and with a realistic estimate of the grip coefficient.