\chapter*{Conclusions}\label{chpt: conclusions}
\stepcounter{chapter}
\addcontentsline{toc}{chapter}{Conclusions}

\section{Research Synthesis and Key Contributions}
This thesis has successfully addressed the foundational engineering trade-off inherent to high-performance  EV traction control: the reconciliation of non-linear tracking robustness with powertrain actuator longevity. While classical linear control architectures may fail to handle severe tire-road friction dropouts without excessive slip overshoot, Traditional Sliding Mode Control introduces high-frequency torque ripples (\textit{chattering}) that can induce incompatibilities with actuators' phyisical limits and  trigger drivetrain resonances.

The primary contribution of this work is the development and virtual validation of a Conditional Integral Sliding Mode Control topology integrated with an adaptive Burckhardt-based Road Estimator Module. By introducing the implementation of a conditional integration block managed by a continuous saturation interpolation within a properly designed boundary layer, high-frequency chattering was entirely extinguished, while completely preventing anti-windup saturation lag during aggressive torque reversals.

\section{Quantitative Performance Verification}
The proposed control architecture was systematically benchmarked against a standard industrial PI controller and Traditional Sliding Mode Control layout across three critical operating conditions within a high-fidelity IPG CarMaker co-simulation environment:
\begin{itemize}
    \item \textbf{Uniform Low-$\mu$ Maneuver:} the CISMC guaranteed exponential convergence onto the optimal slip target during full-acceleration and braking demands, yielding smooth, noise-free steady-state tracking lines.
    \item \textbf{Transient $\mu$-Jump Maneuver:} during sudden changes in road friction, the CISMC successfully prevented the critical wheel spinouts seen in the open-loop configuration. Crucially, the CISMC minimized the total Control Effort to $1.12\times 10^{10}$, representing a massive \textbf{$97\%$ reduction in actuator energy stress} compared to the unmodulated TSMC and a $1.75\%$ improvement over the linear framework.
    \item \textbf{Asymmetric $\mu$-Split Maneuver:} Under cross-track friction imbalances ($\mu_L = 0.1, \mu_R = 0.3$), the CISMC successfully decoupled the independent rear axle dynamics, allowing the high-grip tire to safely maximize its tractive throughput while suppressing localized wheel spinning on the ice-like patch.
\end{itemize}
These results mathematically confirm that the proposed CISMC topology breaks the structural compromise between non-linear stability boundaries and actuator physical preservation.

\section{Future Outlook and Research Directions}
While the virtual validation of the proposed control loop demonstrates high efficacy, several compelling pathways remain open for future academic and industrial extension:
\begin{enumerate}
    \item \textbf{Integration with Full-Vehicle Lateral Dynamics:} The current slip control configuration operates primarily on an independent wheel-by-wheel longitudinal layer. Future work could focus on scaling this topology to cooperate with an upper-level Torque Vectoring and Electronic Stability Control supervisor, actively modulating independent yaw moments to decouple lateral cornering stability from longitudinal traction constraints.
    \item \textbf{Driver Intent Integration in Reference Slip Estimation:} The baseline reference slip architecture focuses primarily on maximizing the instantaneous road friction coefficient. To enhance subjective drivability, future updates could incorporate a refined estimation block that blends environmental adherence limits with the driver's torque request from the accelerator and brake pedals. By dynamically mapping the driver's intent into the reference generation profile, the controller can allow controlled, transient slip variations during aggressive maneuvers to improve responsiveness, while maintaining absolute safety boundaries under steady-state tracking.
    \item \textbf{Regenerative Braking Optimization and Energy Harvesting:} Since the concept vehicle utilizes independent motors, the ABS control law can be expanded into a multi-objective optimization framework during deceleration. Future research could explore a dynamic actuator blending algorithm designed to maximize energy recovery into the high-voltage battery pack. The sliding manifold will act as the core supervisor, distributing the high-frequency slip control effort primarily to the electric motors for regenerative harvesting, and smoothly blending in the hydraulic friction brakes only when satisfying extreme braking torque demands or handling low-speed actuator saturation limits.

    \item \textbf{Hardware-in-the-Loop (HIL) Validation:} To bridge the gap between software-in-the-loop (SIL) co-simulations and real-world implementation, the control code will be deployed on an automotive micro-controller (e.g., dSPACE) interfaced with a physical electric motor testbench, exposing the sliding manifolds to physical signal noise, measurement latencies, and actuator constraints.
\end{enumerate}